METHOD FOR INPUTTING AND PROCESSING FEATURE WORD OF FILE CONTENT

Abstract

A computer or computer retrieval system implemented method for inputting and processing file feature determination information by network terminal users. It includes providing terminal users with the items of the files according to query, determining the input feature word(s) according to the prescribed operation modes and the prescribed modes on the web page on which the item sequence(s) being located or a web page linked by that web page directly. Retrieval system can process the input information to create or improve a retrieval method or database used by users which can include different feature words or classification results, therefore the search efficiency would be greatly improved

Claims

1. A method of enhancing search results using multi-level classification information, comprising: determining multi-level classification information associated with a plurality of data items based at least in part on one or more user inputs and one or more predetermined rules; generating a database, wherein the database comprises the plurality of data items and the multi-level classification information associated with the plurality of data items. retrieving, from the database, at least one of the plurality of data items associated with a search request and multi-level classification information associated with the at least one of the plurality of data items; and generating at least one search results page, wherein the at least one search results page comprises the at least one of the plurality of data items and one or more multi-level classification information indicators associated with each of the at least one of the plurality of data items, wherein each indicator is linked to one or more derivative data items that include corresponding classification information.

2. The method of claim 1, wherein the multi-level classification information associated with the plurality of data items comprises hierarchical classification levels of the plurality of data items.

3. The method of claim 1, wherein the one or more multi-level classification information indicators associated with each of the at least one of the plurality of data items are displayed proximate to a corresponding data item on the at least one search results page.

4. The method of claim 1, wherein the one or more predetermined rules comprise one or more of: (1) a relationship between a user providing a user input and a creator of a corresponding data item; (2) a number of users that provide a similar user input; (3) a time when a user input is made; (4) an accuracy assessment of previous user inputs provided by a certain user or URL; (5) a consistency between a user input and a classification determination made by other methods; (6) whether a user input is from a person who maintains the multi-level classification information or the database; or (7) whether a user or terminal that gives a user input has registered in a website associated with an implementation of the method.

5. The method of claim 1, further comprising: presenting one or more derivative data items that include corresponding classification information in response to selecting a multi-level classification information indicator among the one or more multi-level classification information indicators associated with each of the at least one of the plurality of data items.

6. The method of claim 1, wherein the at least one search results page further comprises a navigation list including a plurality of classification information indicators, wherein each of the plurality of classification information indicators links to one or more derivative data items, and wherein at least some of the derivative data items associated with each of the plurality of classification information indicator comprise corresponding classification information.

7. The method of claim 6, wherein each of the plurality of classification information indicator corresponds to a highest level of classification information associated with the plurality of data items.

8. The method of claim 7, further comprise: displaying one or more corresponding lower levels of classification information in response to a selection of a classification information indicator among the plurality of classification information indicator in the navigation list.

9. The method of claim 6, wherein the navigation list comprises a hierarchy of classification associated with the plurality of data items.

10. A system of enhancing search results using multi-level classification information, comprising, comprising: at least a processor; and at least a memory communicatively coupled to the at least a processor to configure the at least a processor to: determine multi-level classification information associated with a plurality of data items based at least in part on one or more user inputs and one or more predetermined rules; generate a database, wherein the database comprises the plurality of data items and the multi-level classification information associated with the plurality of data items. retrieve, from the database, at least one of the plurality of data items associated with a search request and multi-level classification information associated with the at least one of the plurality of data items; and generate at least one search results page, wherein the at least one search results page comprises the at least one of the plurality of data items and one or more multi-level classification information indicators associated with each of the at least one of the plurality of data items, wherein each indicator is linked to one or more derivative data items that include corresponding classification information.

11. The system of claim 10, wherein the multi-level classification information associated with the plurality of data items comprises hierarchical classification levels of the plurality of data items.

12. The system of claim 10, wherein the one or more predetermined rules comprise one or more of: (1) a relationship between a user providing a user input and a creator of a corresponding data item; (2) a number of users that provide a similar user input; (3) a time when a user input is made; (4) an accuracy assessment of previous user inputs provided by a certain user or URL; (5) a consistency between a user input and a classification determination made by other methods; (6) whether a user input is from a person who maintains the multi-level classification information or the database; or (7) whether a user or terminal that gives a user input has registered in a website associated with an implementation of the method.

13. The system of claim 10, the at least a memory further configuring the at least a processor to: present one or more derivative data items that include corresponding classification information in response to selecting a multi-level classification information indicator among the one or more multi-level classification information indicators associated with each of the at least one of the plurality of data items.

14. The system of claim 10, wherein the at least one search results page further comprises a navigation list including a plurality of classification information indicators, wherein each of the plurality of classification information indicators links to one or more derivative data items, and wherein at least some of the derivative data items associated with each of the plurality of classification information indicator comprise corresponding classification information.

15. The system of claim 14, wherein each of the plurality of classification information indicator corresponds to a highest level of classification information associated with the plurality of data items.

16. The system of claim 15, the at least a memory further configuring the at least a processor to: display one or more corresponding lower levels of classification information in response to a selection of a classification information indicator among the plurality of classification information indicator in the navigation list.

17. A non-transitory computer-readable storage medium bearing computer-readable instructions that upon execution on a computing device cause the computing device at least to: determine multi-level classification information associated with a plurality of data items based at least in part on one or more user inputs and one or more predetermined rules; generate a database, wherein the database comprises the plurality of data items and the multi-level classification information associated with the plurality of data items. retrieve, from the database, at least one of the plurality of data items associated with a search request and multi-level classification information associated with the at least one of the plurality of data items; and generate at least one search results page, wherein the at least one search results page comprises the at least one of the plurality of data items and one or more multi-level classification information indicators associated with each of the at least one of the plurality of data items, wherein each indicator is linked to one or more derivative data items that include corresponding classification information.

18. The non-transitory computer-readable storage medium of claim 17, wherein the multi-level classification information associated with the plurality of data items comprises hierarchical classification levels of the plurality of data items.

19. The non-transitory computer-readable storage medium of claim 17, wherein the one or more predetermined rules comprise one or more of: (1) a relationship between a user providing a user input and a creator of a corresponding data item; (2) a number of users that provide a similar user input; (3) a time when a user input is made; (4) an accuracy assessment of previous user inputs provided by a certain user or URL; (5) a consistency between a user input and a classification determination made by other methods; (6) whether a user input is from a person who maintains the multi-level classification information or the database; or (7) whether a user or terminal that gives a user input has registered in a website associated with an implementation of the method.

20. The non-transitory computer-readable storage medium of claim 17, further comprising computer-readable instructions that upon execution on the computing device cause the computing device at least to: present one or more derivative data items that include corresponding classification information in response to selecting a multi-level classification information indicator among the one or more multi-level classification information indicators associated with each of the at least one of the plurality of data items.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0091] FIG. 1 is the illustration for the applicable environment of the embodiments of the present invention.

[0092] FIG. 2 is an illustrative chart for the feature word (classifier or key word) input on the item sequence page in an embodiment of the present invention.

[0093] FIG. 3 is an illustrative chart for the corresponding feature word indicators (key word indicators) attached to the item or the file it belongs to and navigation list in the page of the item sequence of the search result by user query in an embodiment of the present invention.

[0094] FIG. 4 is an illustrative chart for the corresponding feature word indicator (multi-layer classifier indicator) and navigation list attached to the item or the file it belongs to in the page of the item sequence of the search result by user query in another embodiment of the present invention.

[0095] FIG. 5 is a flow block diagram for the implementation method of an embodiment of the present invention.

DETAILED DESCRIPTION OF THE EMBODIMENTS

[0096] The embodiments of the implementation method are illustrated by reference to the drawings. Wherein, a search engine system 101 is one specialized type of a computer retrieval system 102. They are communicated with user terminal 104 via an Internet 103 (see FIG. 1).

[0097] In the embodiments of the FIG. 2, FIG. 3, FIG. 4, 201 is the query field for inputting query word (classifier or key word), 202 is item (item of topic and abstract), 203 is the query field for feature word (classifier or key word), 204 is a feature word (classifier or key word) determination operation indicator, 205 is a cursor of a mouse device operation, 206 is a reference list of feature words (reference list of classifier or key word), 301 is an indicator of the feature word (key word), 302 is a selection operation indicator, 303 is an operation indicator for adding word, 304 is a navigation list; 305 is an input field for input the query about classifier or key word; 401 is an indicator of the feature word (classifier indicator).

[0098] In the embodiments of the FIG. 5,

[0099] flow 501: search engine system received query requirement from users;

[0100] flow 502: providing an item (topic and abstract) sequence;

[0101] flow 503: inputting the feature word (classifier or key word) and determining the corresponding item or file;

[0102] flow 504: determining the feature word (classifier or key word) of the item or files according to the input;

[0103] flow 505: processing different input opinions;

[0104] flow 506: forming the data, index for the feature word of files;

[0105] flow 507: providing the required item sequence and the feature word (classifier or key word) indicator around each of the item;

[0106] flow 508: providing the required item sequence and a navigation list;

[0107] flow 509: providing the required derivative item sequence and file;

[0108] flow 510: return back.

[0109] To implement the present method, e.g. it should be started with the operation A; firstly, the related retrieval system or search engine system received query request in the query field 201 from network query users or terminal users (flow 501) to provide query searching service to user terminals, which is to provide a sequence made of or partly made of the items of the files (the items of topic and abstract of the files) 202, which is formed by the related retrieval system or search engine system and corresponds to the query request. The files can be from multiple website or database of the related retrieval system or the search engine system (flow 502).

[0110] The said file(s) can be web pages, as well as can include character content and can include image content or audio content or video content.

[0111] The item(s) can be the topic or abstract or topic with abstract or part of the content or the transferred content of the file, such as a web page snapshot, a caching web page, etc.

[0112] The item of the said file can also include different kinds of content, e.g., the abbreviation content of an image, a segment of syllable or score, or a segment or abbreviation content of an audio or video, or a screenshot or a screenshot partial picture.

[0113] The method of the present invention has very significant meaning to create the classification or classification index of the web page or file of image content or audio content or video content.

[0114] The present method also needs to perform the operation B and C (flow 503).

[0115] the operation B: the computer system determines the feature word (classifier or key word) input by terminal users.

[0116] The said feature word (classifier or key word) is a word that determined or inputted by terminal users, which can reflect the feature of the corresponding file or item of topic or abstract or file e.g. key word or classifier, it can also be character(s) or symbol(s) or note(s) or figure(s) or figure mark(s), when needed, for example, it can be a syllable or a score segment relating to an audio file or a video file.

[0117] There are some embodiment operation modes for determination of the input feature word (or the key word or classifier).

[0118] A mode for determination of the input feature word is to regard the word selected by cursor clicking in the feature word list (classification list or key word list) 206 (e.g. the “reference list” 206 in FIG. 2) that presented on the web page on which the said item sequence is located or a linked page or in the feature word list (classification list or key word list) linked directly by the web page as the input feature word (classifier or key word).

[0119] The page or the list linked directly by a page, is the page or the list linked by an item or a feature word (classifier or key word) determination operation indicator or a topic or indicator of list or other word or content on the page on which the item sequence is located.

[0120] When needed, the list of the feature word to be selected will appear on the web page when the terminal web page is in the feature word operation status or in other time.

[0121] Another operation mode is setting “feature word input field” (classifier or key word input field) 203 or an input box on the web page on which the said item sequence is located or a web page linked by that web page directly, the computer system determines the input feature word according to the input content in the input field. The input content of the feature word input field could be from typing, or from a paste of part of the words on the web page on which the said item is located or a web page linked by that web page, or can be allowed to input the feature word to the said input field 203 by means of the cursor click or brush in the item or file or the list of the feature word to be selected.

[0122] The feature word (classifier or key word) input field can be the local space near the indicator or hint word (e.g., “feature word inputting” or “feature word” or “key word” or “classification”) on the web page. The feature word input field can also be the query field on the web page, it can also be configured with a graphic selection key for the corresponding feature word input or query input.

[0123] It is needed to make the terminal web page staying in the feature word operation status, which can be presented by the query system, or by the clicking selection of terminal users. When needed, it also can be prescribed that when the operation indicator 204 of the feature word determination on the web page or the list 206 of the feature word to be selected or the feature word input field 203 is being clicked or with the input content, the terminal web page enters or stays in the feature word operation status.

[0124] The so-called selecting click can make the cursor in clicking status to slip over the related word, or can be the other prescribed operation modes. When implementing in embodiments, it is better to cooperate with clicking “the feature word determination operation indicator” (classifier or key word determination operation indicator) 204 before or after, or make the terminal page staying in the feature word (classifier or key word) operation status by other means to benefit the computer identification

[0125] The said “feature word (classifier or key word) determination operation indicator” (called operation indicator for short) means by using which to receive a click to enter into a feature word operation mode, or to indicate the item or file corresponding to the feature word (classifier or key word), or to link the feature word list (classification list or key word list) to be selected. The operation indicator can be the character or indicator or figure or graphic key of other related operation, such as the word sample like “determining feature word” 204 or “linking feature word list” or “classification operation indicator” or “participating in classification”, etc. in FIG. 2.

[0126] It is also needed that the computer system determines the item (items of topic or abstract) or file corresponding to the input feature word according to one of the following modes on the page on which the said item sequence is located or a web page linked by that page (operation C) (flow 503).

[0127] Specifically speaking, the mode I can be used as: the item 202 or file in which the word 208 selected by the said cursor clicking in one operation mode 1 in operation B is determined to be the item or file corresponding to the input feature word.

[0128] Or mode II: the item or file being clicked is determined to be the item 202 or file corresponding to the input feature word. It's better for the terminal page to stay in the feature word operation status.

[0129] Or mode III: the item or file around the clicked feature word determination operation indicator 204 is determined to be the item or file corresponding to the input feature word.

[0130] Or mode IV: the item or file is determined to be the item or file corresponding to the input feature word if the item or file is the nearest to the input field or on the prescribed (e.g. the upper or lower) location to the input field on the web page on which the feature word input field is located.

[0131] Or mode V: the only item or file on the web page with the feature input field is determined to be the item or file corresponding to the input feature word (classifier or key word).

[0132] Or mode VI: it is determined to be the item or file corresponding to the input feature word (classifier or key word) by the item or file which is the nearest to the list on the web page that the said list of the feature word (classification list or key word list) to be selected or on the prescribed location or direction (e.g., the left or right direction) of the list.

[0133] Or mode VII: the only item or file on the web page on which the list of the feature word (classification list or key word list) to be selected is determined to be the item or file corresponding to the input feature word (classifier or key word).

[0134] In fact, it can be arranged, as needed, for the order of the operation B and operation C as well as the operation rule of the terminal users.

[0135] The said list of the feature word (classification list or key word list) to be selected can be composed of many words being referred or selected when inputting the feature word (classifier or key word).

[0136] The list can be with a title like a “reference list” or a “classification list” or a “key word suggestion”.

[0137] In one embodiment, we can set the words like “recommended keyword:” or “selected classifier:” below each item to create an input field to benefit the user input. In order to avoid an error operation, the input field can be followed with the words “selection accomplishment” to confirm by clicking. Therefore, the user only need to input or “paste” in with the keyword or classifier in the input field of the corresponding item, and then click “selection accomplishment:” to accomplish the determination of the feature word of the file. This embodiment makes use of the said operation mode 3 and mode IV.

[0138] In another embodiment of this invention, there is the word “classification” (the feature word determination operation indicator) on the lower side or end of each item. After being clicked by a user, highest-layer classifiers of the list of the feature words to be selected would appear on one side of the web page. After the user clicking the classifier among them, there would be many classifiers belonging to the lower layer of the classification to be selected by the user. Analogically, when the user accomplishing selection and clicking the word “select”, each of the classifiers in the multi-layer classification of the item will be automatically input by the system. This embodiment makes use of the said operation mode 2 and mode III.

[0139] In the embodied implementation process, the operation mode 1 and mode I can also be used;

[0140] Or the operation mode 2 and mode II can also be used;

[0141] Or the operation mode 2 and mode VI can also be used;

[0142] Or the operation mode 2 and mode VII can also be used;

[0143] Or the operation mode 3 and mode III can also be used;

[0144] Or the operation mode 3 and mode V can also be used;

[0145] Or the operation mode 3 and mode VI can also be used;

[0146] Or the operation mode 3 and or mode VII can also be used, to determine the feature word or key word or classifier for the corresponding item in the item sequence or the corresponding file.

[0147] The present method is allowed providing a kind or many kinds or many suits of the feature word list or the keyword list or the classifier list (classification list or key word list) or multi-layer classifier list to be select for user terminals.

[0148] It can be generally acknowledged that the feature word of a certain item is the same or similar to the feature word of the file belonging to the item, the feature word of the file belonging to the item can be directly obtained according to the feature word of a certain item, or be determined in reverse.

[0149] Obviously, the input feature word in the present method is the determination information about the feature of the related item or file or the feature word corresponding to the feature inputted by clicking on the terminal from an operator.

[0150] The method can also include that the related computer system can be received or referred to or processed or denied with the feature determination opinion or feature word or classifier inputted by the terminal user.

[0151] Thus, it is the input that the feature word or keyword or classifier information of the related item or file by clicking on the terminal from an operator according to the operation A, B, C, namely, 504 “determining the feature word of the item or files according to the input”. The computer system or retrieval system can make use of this information directly, but may also need to process the input classification information.

[0152] Obviously, there is also a problem in the determination of the feature word for each file according to the clicking selection by Internet user: if there are different choices from the multiple users or terminal operators, what should to be done? That is the problem to be solved in “processing different input opinions” in the flow 505 in Figure.

[0153] When the retrieval system facing with the potential contradictory opinions input by the users or terminal operators to determine or input the feature word or classifier corresponding to any one item or file, the principles need to be followed can be at least considered about one or more of the following factors:

[0154] (1) The similarity between the title of the user who makes determination or the website URL and the topic of the file provider or author or its URL or the URL linking to the file; the more they like, the possibility of consistency between the user of classification selection and the provider of the original file is higher.

[0155] (2) The number of the users who made the same determination;

[0156] the higher the number of the users who made the same determination is, the more reliable the opinion is.

[0157] (3) The earlier or later for the time making a certain determination;

[0158] in order to form a classification index as quick as possible, it cannot be waited for too long; but the later revised opinion could be more cogent.

[0159] (4) The accuracy or score for the previous clicking selection from the user who makes determination or the same URL;

[0160] the opinion made by the users with high scores should be paid with more attention to.

[0161] (5) The consistency between the result of the selection by this kind of feature word and other artificial selection methods or computer selection methods or other selection system;

[0162] This will not only help you access to the existing achievement but also avoid changing too much.

[0163] (6) Whether the determination made by the retrieval system operator or staff or the like.

[0164] (7) Whether the user or the terminal who makes determination has registered in the website or web page which is relevant to the feature word determination or selection.

[0165] In fact, (1) or (6) or (7) can be given priority when needed and then consider other factors.

[0166] The formula for a certain objective function can also be edited, the variables of the function formula at least include one or more of the seven factors said above. The priority on the different classifications can be determined according to the objective function value.

[0167] The number of the feature words (especially the key words) for any one item or file might be high, the priority order of the feature words can be arranged by reference to the above factors and the highest number of the retained or provided feature words can be properly limited.

[0168] In fact, the classifier or feature word in the same layer or the classification selection for any one of the item or file is not necessary to be only one, it might be two or more, and have a priority order. It can limit the number of the classifier on each layer for any one item or file, for example, 5 or 6 or 8.

[0169] In the practice, a user who would like to determine the feature words or classification words of a file or an item may need to do multiple searches and determine on their own articles or interesting files to them. Therefore, the process from 501 to 505 needs to be repeated for several times. When the files which have been determined accumulate to a sufficient amount, applicable search tool setup can be proceeded with through this method. For an instance, we can create feature words index (classifier or key word index) or form new search modes so as to fundamentally improve search results in future. Furthermore, this method can also regard the feature words of one or more items or files or its consistency or discrepancy as the determinants for the rankings of files or items in search results.

[0170] For example, this method will encourage all network terminal users to include authors' names when they make determinations on searched files or items. As such, many files will be added with authors' information. Search engines can not only make files or items owned by hot authors or with hot feature words appear in former pages of search results, but it can also enable the files or items owned by different authors or with different feature words to appear and to be equally distributed in former pages of search results.

[0171] The method of this invention can also include 506 “forming the data, index for the feature word of files”: the retrieval system generates the database including the feature word content of multiple files or items or the database classified by the feature words or the classification by difference wholly or partly according to the data of the feature words (classifier or key word) corresponding to the multiple items or files determined by the said method, and generates the feature word index of the multiple files or items, which can be including: classifier index, classification index, keyword index, the feature word reversal index, keyword reversal index, classification reversal index, the item reversal index, etc. The reversal index is well known by people.

[0172] The said feature word index can refer to that by using the index, it can be retrieved or accessed to or linked to the file or its item or its address or its related information corresponding to the feature word according to any one of the selected feature words.

[0173] By the said feature word index (classifier or key word index), a computer retrieval system can provide the files or its items corresponding to the feature word according to the query of network terminal users.

[0174] It can be retrieved or accessed to or linked to the file or its item or its address or its related information corresponding to the classifier according to any one of the selected classifiers.

[0175] When needed, it can also be generated the classification database of the files or the items including multiple different subsets or multi-layer subsets or the multi-layer classification index according to each feature word or keyword or classifier of the item or file.

[0176] The method in the present method can also include: other original classifications or classification index for the multiple files can be replaced or revised by the classification or classification index for the feature word of the multiple file by using the method.

[0177] In the flow 504 or flow 506, it can be referred back (flow 510) to the flow 501 if the terminal user wishes to begin a feature word determination to other item or file.

[0178] Obviously, the purpose of this invention is not only to build a feature word database or feature word reversal index of related files, but it can also include performing item searching by using the index or data.

[0179] The present method can also include: when receiving a query, the retrieval system provides the retrieval or search result that is corresponding to the need of the feature word or classifier. The result can include an item (item of topic and abstract) or an item sequence or a list or a tree catalogue. An input field (305) can be set for input the query about classifier or key word (s) on the web page (FIG. 3 or FIG. 4) provided by computer retrieval system, for providing the search result that meeting the demand of the classifier(s) or key word.

[0180] The present method can also include:

[0181] The computer retrieval system provides the item sequence of multiple files to user terminals, there can respectively be the feature word indicator (301 or 304) for each of the item or the file belonging to the item around each of the item in part or whole of the said item sequence (flow 507).

[0182] The said feature word indicator can also be the key word indicator 301 related to the item or the belonging file (FIG. 3).

[0183] The feature word indicator of each item or the belonging file can be a single-layer or multi-layer classification indicator 401 (See in FIG. 4).

[0184] The classification indicators is the indicators of the classifiers or classification of the item. They are words or word graphic keys representing the classifications of the item. The so-called multi-layer classification indicators are suitable for many classifications which belong to the different layers of the classifications of the item or the belonging file.

[0185] Obviously, each classifier of the so-called multi-layer classifier indicators, no matter how big the classification is, it is the belonging classifier of the item or the belonging file. Thus when comparing with the generally displayed tree catalogue or the ordinary navigation list, there is not only a great decrease in the occupying space, but also a direct prompting and representative for the related items.

[0186] For example, a certain file or item belongs to the classifier “science”, in the next layer of sub-classification it belongs to the classifier “theory”, in the lower layer of sub-classification it belongs to the classifier “physics”. The words like “science, theory, physics” 401 around the item would be regarded as the indicators of multi-layer classifier.

[0187] The keyword in the said keyword indicator related to the item reflects the feature of content of the item or the belonging file.

[0188] There can be many methods to realize adding or displaying of the multi-layer feature word (or keyword or classification) indicator belonging to the item around the item. One is to make use of the address or URL of the belonging file corresponding to the item to access to the file, and further obtain the feature word (or keyword or classifier) information of the file (by using the result in 506), and add the word(s) around the original item. Another method is to directly display each item with the multi-layer feature word (or keyword or classifier) information of the original file when generating the item reversal index of the keyword or query word of the file with the feature word information of itself. Or other methods can be used.

[0189] We can make the feature word indicator around the said item link to the derivative item sequence of the other multiple file respectively 509. The feature word (or keyword or classifier) of the part or whole of the items of the linked derivative item sequence or the belonging file is the same to the feature word (or keyword or classifier) of the original indicator linked to the sequence, and can be or not be in accordance with the query request provided by the original user.

[0190] When needed, for example, the derivative item sequence of the files that belongs to the feature word and corresponds to the query request by the original user can be obtained when the search user clicking a certain feature word indicator in the multiple indicators to be selected (flow 509), thus the searching area can be greatly reduced or freely controlled to obtain the query result and the demanded file.

[0191] Obviously, around the said new obtained item in the derivative item sequence of the file corresponding to the feature word, there can also be the multiple different feature words indicators (or classification indicators or keyword indicators) belonging to the item or the belonging file simultaneously, it can also be made that the multiple feature word indicator (or classifier indicator or keyword indicator) belonging to the file which belongs to the item links to the other derivative sequences of the multiple item related to these indicators, and the rest may be deduced by analogy.

[0192] Sometimes, there might be a multi-layer classification list (e.g., the international classification list for patent literature) in a specific scope in the existing retrieval technologies, but the unprofessional ordinary user usually cannot grasp the meaning or the exact covering scope of each classifier and make the wrong selection of classification, which affects the retrieval speed.

[0193] Some search engine systems provide the indicator e.g. “the similar web page” or “the same website” and the like at the end of the item for the search result, but the obtained result is too general and disordered, and the usage is very limited.

[0194] However, the method of this invention, which simultaneously displays the indicator of the multiple feature word around the provided item when queried, can bring great convenience to the query maker. When the user found the interested item, if he or she wants to obtain a sequence of items belong to the higher layer classification of the interested item, the higher layer feature word or classifier (e.g. “science” in the previous illustration) in the indicators can be clicked; if he or she wants to obtain a sequence of items belong to the lower layer classification of the interested item, the lower layer feature word or classifier (e.g., “physics” in the previous illustration) in the indicators can be clicked directly. Therefore, the accuracy and flexibility of the clicking selection by the query maker can be maintained meanwhile. The query efficiency and query experience can be improved.

[0195] The linkage between the said classifier indicator or keyword indicator and the new derivative item sequence in the present invention can be a direct linkage or an indirect linkage 509.

[0196] The said indicator can firstly be linked to the query search in which added the feature word (or the corresponding classifier or the keyword) in the indicator as a query word to the original query word, and thus obtain the demanded sequence.

[0197] The said indicator can firstly be linked to the query search, which regard the feature word or corresponding classifier or keyword in the indicator as the query logical requirement further on the basis of the original query, and thus obtain the demanded item sequence.

[0198] When needed, the item(s) presented in the original query result sequence while not presented in the said derivative item sequence can be arranged to follow the said derivative item sequence.

[0199] It can be arranged that, when needed: around the item sequences of the multiple files provided by the computer retrieval system to the user terminal according to the query request submitted by the network query user, there is a navigation list composed by the multiple feature word indicators (flow 508), each of the feature word indicators can link to a different derivative item sequence of multiple files respectively.

[0200] Namely, if the user clicking a certain feature word in the list when searching (it can be arranged as needed to re-clicked the “search” or “confirm” or the operation key with other titles), the new derivative item sequence corresponding to the feature word would be obtained 509, the feature word of the file belonging to the item in the sequence is the same to the feature word in the original indicator (the clicked) linked to the sequence, and can be in accordance with the original query request from the user or not.

[0201] The said navigation list can be a one layer list or a multi layer list. It can be allowed to automatically display multiple feature word indicators in the next layer to be selected after determining the selection of the feature word of the upper layer of the list.

[0202] The said feature word indicator of the navigation list can be a classifier indicator or a keyword indicator.

[0203] The linking between the feature word indicator of the said navigation list and the new item sequence can be a direct linking or an indirect linking.

[0204] The said indicator can firstly be linked to the query search, which add an indicator demand for the keyword in the indicator on the basis of the original query word, and thus obtain the demanded item sequence. The said indicator can firstly be linked to the query search, which regard the feature word in the indicator as the query logical requirement further on the basis of the result of the item sequence searching of the original query, and thus obtain the demanded item sequence. When needed, the item in the original item sequence while not presented in the item of the new item sequence can be arranged to follow the new item sequence. When needed, the flow 507 or 508 can be repeated on the item sequence of the flow 509 to make it has the corresponding feature word indicator or navigation list to link or display the updated result of the item sequence by clicking.

[0205] When accomplishing the search, the searcher can return (flow 510) to begin the operation again.

[0206] The above content is the illustrative description for the method in this invention, which cannot be used to limit the claims scope of this invention.