Methods and apparatus consistent with the invention provide the ability to organize and build understandings of machine data generated by a variety of information-processing environments. Machine data is a product of information-processing systems (e.g., activity logs, configuration files, messages, database records) and represents the evidence of particular events that have taken place and been recorded in raw data format. In one embodiment, machine data is turned into a machine data web by organizing machine data into events and then linking events together.

A method includes hierarchically identifying occurrences of some of the words in the set of sentences; creating a first index for each of some of the words based on the upper hierarchy of occurrences identified for each word; receiving input of a queried word; hierarchically identifying occurrences of the queried word in the set of sentences; creating a second index based on the upper hierarchy of occurrences identified for the queried word; comparing the first index and the second index to calculate an estimated value for the number of occurrences of a word in the neighborhood of the queried word; and calculating the actual value of the number of occurrences of a word in the neighborhood of the queried word based on an upper hierarchy and lower hierarchy of the occurrences on condition that the estimated value is equal to or greater than a predetermined number.

In an approach to automating multilingual indexing, a computer receives text of a conversation between at least two users. The computer detects at least one language associated with the text. The computer determines whether the language associated with the text is detected with a confidence level that exceeds a threshold. The computer retrieves text from one or more previous conversations between the two users. The computer detects at least one language associated with the text. The computer determines whether the at least one language associated with the text is detected with a confidence level that exceeds a pre-defined threshold. The computer analyzes the text using at least one of the detected languages to create one or more terms. The computer indexes the one or more terms and stores a boost value associated with each of the one or more indexed terms corresponding to confidence level of the detected language.

Methods and systems for providing a search engine capability for large datasets are disclosed. These methods and systems employ a Partition-by-Query index containing key-values pairs corresponding to keys reflecting concept-ordered search phrases and values reflecting ordered lists of document references that are responsive to the concept-ordered search phrase in a corresponding key. A large Partition-by-Query index may be partitioned across multiple servers depending on the size of the index, or the size of the index may be reduced by compressing query-references pairs into clusters. The methods and systems described herein may to provide suggestions and spelling corrections to the user, thereby improving the user's search engine experience while meeting user expectations for search quality and responsiveness.

According to one embodiment, an electronic device includes a memory that stores files and a hardware processor. The hardware processor determines, if a first keyword is input, first files including the first keyword, of the files, determines a first period to classify the first files with respect to dates of generation or dates of updating, and a second keyword to classify the first files, displays a first icon indicative of a first group of the first files which have been generated or updated in the first period and which include the second keyword, and displays the first files which have been generated or updated in the first period and which include the second keyword if the first icon is selected.

According to one embodiment, an electronic device includes a memory that stores files and a hardware processor. The hardware processor determines, if a first keyword is input, first files including the first keyword, of the files, determines a first period to classify the first files with respect to dates of generation or dates of updating, and a second keyword to classify the first files, displays a first icon indicative of a first group of the first files which have been generated or updated in the first period and which include the second keyword, and displays the first files which have been generated or updated in the first period and which include the second keyword if the first icon is selected.

A method of performing auto-naming of content includes: receiving an auto-naming command for the content; performing auto-naming of the content by using different parameters according to different content types to obtain at least one auto-naming result for the content; and displaying the auto-naming result.

The invention relates to a method used by computers for searching words in documents written in a source language, which are not in the vocabulary of said source language, but are transcript of meaningful words in an origin language. The method is comprised of a preparation process and a search process. During the preparation process a database of unrecognized words in the source language is maintained, which contains, among other data, normalized phonetic conversion of the unrecognized word, as well as a corpus of all words of the documents in the search domain and indexes for efficient search. During search, a phonetic conversion and normalization is done for the search word, and the distance to similar phonetics words in the corpus is calculated. The found words in the corpus are arranged in ascending order, and the relevant

A method and client device is disclosed for indexing content of a multimedia file. The method comprises using a client device to segment the content of the multimedia file into a plurality of segments and to determine structure-searchable data for each segment. Determining structure searchable data for a segment comprises (1) identifying one or more features of respective multimedia types in the segment; (2) correlating each of the identified features to one or more respective keywords; and (3) calculating one or more respective relevance factors for each of the keywords, where at least one of the relevance factors is based on one or more characteristics of the client device. The method also comprises the client device transmitting the structure-searchable data (including the keywords, relevance factors, and respective media types of the identified features) to an indexing server.

Methods and systems for mapping repairs orders within a database are described. Mapping a repair order can include generating a searchable data record with multiple data record fields. Each data record field can include a term located on the repair order or a standard term associated with the term on the repair order. In order to retrieve repair orders from the database, the data records can be searched using search criteria that match standard terms storable in the data record fields. Although the repair orders can be searched to find repair orders with terms that match the search criteria, the search may be carried our more efficiently (e.g., quicker) by searching the data records instead of the repair orders. One or more repairs orders can be associated with real-fix tips. Phrases of the real-fix tips can be selected automatically based, for example, or RO terms recited on the repair orders.