METHODS AND SYSTEMS FOR MODIFYING A USER PROFILE FOR A RECOMMENDATION ALGORITHM AND MAKING RECOMMENDATIONS BASED ON USER INTERACTIONS WITH ITEMS
20170316088 · 2017-11-02
Assignee
Inventors
Cpc classification
G06F16/437
PHYSICS
International classification
Abstract
Methods and apparatus for modifying a user profile for a recommendation algorithm are provided. A user is provided with electronic access to an item. The item may comprise one of a document, an article, a chart, a graphic, a report, a web page, or the like. User interaction with the item is enabled. The user interaction with the item is then electronically tracked and stored. The user's user profile used by a recommendation engine is then modified based on the tracked user interactions. The user interaction may comprise at least one of annotating, highlighting, modifying, customizing, adding comments to the item, and the like. The user modified item can be saved and details of the user interaction with the item may be used to modify the user profile. At least one of items or peer recommendations can then be provided to the user based on the modified user profile.
Claims
1. A computerized method for modifying a user profile for a recommendation algorithm, comprising: providing a user with electronic access to an item, the item comprising one of a document, an article, a chart, a graphic, a report, and a web page; enabling user interaction with the item; electronically tracking and storing the user interaction with the item; and modifying the user's user profile used by a recommendation engine based on the tracked user interactions.
2. A method in accordance with claim 1, wherein the user interaction comprises at least one of annotating, highlighting, modifying, customizing, and adding comments to the item.
3. A method in accordance with claim 2, wherein the user interaction is enabled via an application service provider application or a downloadable software application.
4. A method in accordance with claim 2, further comprising: enabling a web page displaying the item to be displayed as an interactive web page providing capabilities for at least one of entering annotations, entering comments, adding highlighting of text portions, and making modifications to the item.
5. A method in accordance with claim 4, further comprising: saving the user modified item; recording details of the user interaction from the user modified item; using the details of the user interaction to modify the user profile.
6. A method in accordance with claim 5, wherein the details of the user interaction comprise at least one of: a coordinate position of the annotation, modification, comment, or highlighting in the item; the content of the annotation, modification, comment, and highlighting; meta data describing the content being annotated, modified, commented on, or highlighted; meta data assigned to the annotation, modification, comment, or highlighting; and results of sentiment analysis of the annotation, modification, comment, or highlighted content.
7. A method in accordance with claim 6, wherein the user profile is modified based on at least one of: key words taken from the annotation, modification, comment, or highlighted content; meta data describing the annotation, modification, or comment; key words from the highlighted content; meta data of a highlighted section; and meta data describing the item being modified in an info-graphic interface.
8. A method in accordance with claim 1, wherein the user profile is stored in a database and modified at least one of: periodically at defined intervals; after each user interaction; after a defined number of user interactions; and after a number of user interactions supersede a predetermined threshold number of interactions.
9. A method in accordance with claim 1, wherein one of: the user accesses the item via a web site, a mobile application, or interactive email; the item is provided to the user via the recommendation engine; and the item is accessed from a database.
10. A method in accordance with claim 1, wherein: the item comprises an info-graphics chart with weighted data elements; the user interaction comprises modification of one or more weights assigned to the data elements.
11. A method in accordance with claim 10, wherein: the info-graphics chart may comprise an X axis and a Y axis; the X axis and the Y axis each correspond to weighted sums of sub scores along multiple sub-dimensions; weights are assigned to each sub-dimension; user modification of the weight for a particular sub-dimension indicates a relative priority of the particular sub-dimension to the user.
12. A method in accordance with claim 11, wherein: user modification of the one or more weights is enabled via an interactive graphics display comprising one of a slidebar for each of the weights, a clickable weight scale for selecting the desired weight for each sub-dimension, a user interface embedded in a web page providing the info-graphic, and an editable table listing the weights for each sub-dimension.
13. A method in accordance with claim 1, further comprising: providing at least one of items or peer recommendations to the user based on the modified user profile.
14. A method in accordance with claim 13, wherein items or peer recommendations provided to the user are modified based on the modified user profile.
15. A method in accordance with claim 14, wherein modifications to the items or peer recommendations comprise at least one of highlighting of key words in a recommended document, creating a custom view in an info-graphics chart, re-ordering of text elements in the recommended document, inserting annotations into an item, cropping or customizing of the info-graphics chart, providing customized contextualized comments to the recommendations which relates the recommendations to the modified user profile, and re-ordering a list of recommendations.
16. A method in accordance with claim 1, wherein the user profile in an unmodified state comprises at least one of an explicit profile comprising data entered by the user and an implicit profile comprising information obtained from user behavior.
17. A method in accordance with claim 16, wherein the user behavior comprises at least one of key words used in key word searches, articles reviewed, web pages reviewed, articles purchased, discussions reviewed, discussions participated in, peer profiles selected for connection, articles or web pages saved or downloaded, and items clicked on in an info-graphics chart.
18. An apparatus for modifying a user profile for a recommendation algorithm, comprising: a user interface providing a user with electronic access to an item, the item comprising one of a document, an article, a chart, a graphic, a report, and a web page, and enabling user interaction with the item; a software application for electronically tracking the user interaction with the item; a database for storing the user interaction with the item; a database for storing a user profile; wherein: the software application modifies the user profile based on the tracked user interactions; and the modified user profile is used by a recommendation engine to serve items or peer recommendations to the user tailored to the modified user profile.
19. A method for providing recommendations using a continuously modifiable user profile, comprising: entering an initial user profile; providing a user with electronic access to an item, the item comprising one of a document, an article, a chart, a graphic, a report, and a web page; enabling user interaction with the item; electronically tracking and storing the user interaction with the item; modifying the initial user profile based on the tracked user interactions; and serving one or more items or peer recommendations to the user based on the modified user profile.
20. A method in accordance with claim 19, wherein the one or more items or peer recommendations served to the user are at least one of modified and customized by the recommendation engine based on the modifications to the user profile.
21. A system for providing recommendations using a continuously modifiable user profile, comprising: a user interface providing a user with electronic access to an item, the item comprising one of a document, an article, a chart, a graphic, a report, and a web page and enabling user interaction with the item; a software application for electronically tracking the user interaction with the item; a database for storing the user interaction with the item; a database for storing a user profile; a recommendation engine for serving items to users based on the user profile; wherein: the software application modifies the user profile based on the tracked user interactions; and the modified user profile is used by a recommendation engine to serve one or more items or peer recommendations to the user tailored to the modified user profile.
22. A system in accordance with claim 20, wherein the one or more items or peer recommendations served to the user are at least one of modified and customized by the recommendation engine based on the modifications to the user profile.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
[0028] The present invention will hereinafter be described in conjunction with the appended drawing figures, wherein like reference numerals denote like elements, and:
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DETAILED DESCRIPTION
[0037] The ensuing detailed description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the invention. Rather, the ensuing detailed description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an embodiment of the invention. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the invention as set forth in the appended claims.
[0038] The present invention relates to the provision of the ability to continuously update, modify, supplement, and/or customize a user profile for use in a recommendation algorithm based on a user's interaction with an item or object that is either provided by the recommendation algorithm to the user or available to them otherwise, provided that the interaction of such item can be tracked or monitored (whether in real-time or subsequently) by the recommendation system. The user can also be provided with the ability to directly modify and customize certain elements of his/her profile, for example, by changing or modifying various weighting factors or reordering elements, as will be explained in more detail below.
[0039] It should be appreciated that the term “user” as used herein may be interpreted to mean an individual, a company, an association, an organization, a collection of individuals, or the like.
[0040] One example of a recommendation engine is disclosed in commonly-owned co-pending U.S. patent application Ser. No. 13/528,029 filed on Jun. 20, 2012 entitled Bi-Model Recommendation Engine for Recommending Items and Peers, which is respectfully incorporated herein and made a part hereof by reference. The present invention can be used in connection with the recommendation engine described in U.S. patent application no. Ser. No. 13/528,029.
[0041] In one example embodiment of the present invention, a computerized method for modifying a user profile for a recommendation algorithm is provided.
[0042] The user may access the item 17 via a web site, a mobile application, an interactive email, or the like via the Internet-enabled device 10. Alternatively, the item 17 may be provided to the user via a recommendation engine 14, or the item 17 may be accessed from a database 16 or other trackable source (e.g., remote server 30 or other Internet source).
[0043] Those skilled in the art should appreciate that the connections between the elements of
[0044] User interaction with the item 17 is enabled. The user interaction with the item 17 is then electronically tracked and stored (e.g., via an interaction database 18 and associated tracking software 19). The user's user profile 21 (e.g., stored in a profile database 20) used by the recommendation engine 14 may then be modified based on the tracked user interactions. Although the tracking software 19 is shown in
[0045] The user interaction may comprise at least one of annotating, highlighting, modifying, customizing, adding comments electronically within the item 17, or otherwise personalizing the item 17. The user interaction may be enabled via an application service provider application or a downloadable software application resident on the Internet-enabled device 10. The Internet enabled device 10 may comprise a computer, laptop, personal computing device, tablet, e-book reader, smart phone, or the like.
[0046] A web page displaying the item 17 may be enabled to be displayed as an interactive web page providing capabilities for at least one of entering annotations, entering comments, adding highlighting of text portions, making modifications to the item, and the like. For example, when viewing the item, the user may click on an “annotate” icon, which causes the page being viewed to be displayed as an interactive page with editorial functions consistent with the present invention, including highlighting, annotating, modifying, customizing, commenting, and the like.
[0047] In one example embodiment, the method may further comprise saving the user modified item 17 (e.g., in database 16), recording details of the user interaction from the user modified item 17 (e.g., in interaction database 18), and using the details of the user interaction to modify the user profile 21, which may be stored in the profile database 20.
[0048] The details of the user interaction stored in the interaction database 18 may comprise at least one of: a coordinate position of the annotation, modification, comment, or highlighting in the item; the content of the annotation, modification, comment, and highlighting; meta data describing the content being annotated, modified, commented on, or highlighted; meta data assigned to the annotation, modification, comment, or highlighting; results of sentiment analysis of the annotation, modification, comment, or highlighted content, and any similar methods which capture the essence of the modification.
[0049] The user profile 21 may be modified based on at least one of: key words taken from the annotation, modification, comment, or highlighted content; meta data describing the annotation, modification, comment; key words from the highlighted content; meta data of a highlighted section; meta data describing the item being modified in an info-graphic interface, and the like.
[0050] Alternatively, once the user has completed reviewing and modifying the item 17, the annotated item 17 is saved on a remote server 30 (rather than database 16) for future use (both by the user and by the recommendation engine 14). The remote server 30 may then record the annotation details as discussed above and save this information under a user ID. The user can also save the item locally (on the Internet-enabled device 10 or a storage device associated therewith) as a PDF file for printing and sharing purposes. In such an embodiment, the remote server 30 may also include tracking software 19 and be in communication with both the recommendation engine 14 and the profile database 20, such that the user profiles can be updated in the same manner as discussed above. It should be appreciated that, although the recommendation engine 14 and other components shown in
[0051] The user profile 21 may be stored in the profile database 20 and modified at least one of: periodically at defined intervals; after each user interaction; after a defined number of user interactions; after a number of user interactions supersede a predetermined threshold number of interactions, and the like. Software 15 for use in modifying the user profile may be provided in the profile database 20. Although the profile modification software 15 is shown in
[0052] In another example embodiment as shown in
[0053] As shown in
[0054] User modification of the one or more weights may be enabled in a variety of ways. For example, as shown in
[0055]
[0056] While the above-embodiments of present invention are described herein in connection with Gartner's Magic Quadrant, those skilled in the art should appreciate that it can be applied to any info-graphics chart from any provider, as well as to any type of business metric, graph, table, or the like where weighting factors and/or scores are used.
[0057] For example, with the present invention, the user may receive a recommendation to access, or otherwise accesses or views, a Magic Quadrant or other info-graphics chart (e.g., via an interactive web page or a software application), which provides the Gartner view with the Gartner calculated coordinates, and the user is allowed to create a custom view by modifying the weights 34 for each of the sub dimensions, and hence, recalculating vendor positions along X and Y coordinates. For example, the user may feel that the sub-dimension “sales execution and pricing” is of critical importance, and increase the weighting factor applied to this sub-dimension, resulting in vendors having a higher score in this area being given an upgraded position in the Magic Quadrant. The system then records and saves the customized view in the user's extended profile or a similar table, which can then be applied to further recommendations for that user.
[0058] It should be appreciated that access to the info-graphics, such as the Magic Quadrant, can be provided in a variety of ways, including but not limited to via an interactive web page or a software application (either provided remotely via an application service provider or a downloadable application resident on a computer, laptop, personal computing device, tablet, e-book reader, smart phone, or the like).
[0059] Once the user has adjusted the weightings 34, the resultant custom view of the info-graphics is saved for future use, for example on a database 16 or remote server 30. The database 16 or remote server 30 records the custom weight table for the particular user, for example under an info-graphic ID assigned to that user as part of the user profile 21 (as described above).
[0060] It is also contemplated that the info-graphics may be modified “off line” apart from the system or the corresponding software application, and later uploaded to the system and/or stored at the database 16 or server 30. The changes in the weighting details can then be processed as discussed above.
[0061] At least one of items or peer recommendations may be provided from the recommendation engine 14 to the user based on the modified user profile 21. Further, the items or peer recommendations provided to the user may be modified based on the modified user profile 21. For example, modifications to the items or peer recommendations may comprise at least one of highlighting of key words in a recommended document, creating a custom view in an info-graphics chart, re-ordering of text elements in the recommended document, inserting annotations into an item, cropping or customizing of the info-graphics chart, providing customized contextualized comments to the recommendations which relates the recommendations to the modified user profile, re-ordering a list of recommendations, or the like.
[0062] The user profile 21 in an unmodified state may comprise at least one of an explicit profile comprising data entered by the user and an implicit profile comprising information obtained from user behavior. The user behavior may comprise at least one of key words used in key word searches, articles reviewed, web pages reviewed, articles purchased, discussions reviewed, discussions participated in, peer profiles selected for connection, articles or web pages saved or downloaded, items clicked on in an info-graphics chart, and the like.
[0063] In addition, the present invention also encompasses methods and systems for providing recommendations using a continuously modifiable user profile.
[0064] The one or more items 17 or peer recommendations served to the user may be at least one of modified and customized by the recommendation engine 14 based on the modifications to the user profile 21. For example, it can highlight key words in a new item it serves in advance, based on the user's recorded recent highlights. In another example, the recommendation engine may also create a custom view in a new Magic Quadrant it serves based on the user's recently recorded custom weights. Additional modifications to recommended items may also be provided by the recommendation engine based on the modified user profile, such as re-ordering of text or elements of an item, inserting annotations into an item that relate to a user's comments or annotations in a recently modified item, cropping and/or customizing info-graphics based on user's customization of similar graphics, as well as other conceivable modifications.
[0065] Such methods and systems for providing recommendations may implement the various embodiments of the methods for modifying a user profile discussed above.
[0066] It should be appreciated that the process described above in connection with
[0067] With the present invention, the user's interests and priorities at a given point of time are implicitly and explicitly derived from the richness provided by the spectrum of the user's recent interactions with, and modifications of, an information item or items. Inputs such as annotations, highlights, saved comments, and modifications of info-graphics, provide valuable data about the user's interests and priorities beyond the value provided by the binary signals already available (for example, coordinates of highlighted paragraphs vs. a binary signal “read the document=yes”). This data, once aggregated, tabulated, prioritized (by date, significance, depth of interaction, etc.), and mapped to the relevant taxonomy, can be used in order to calculate to time-sensitive relevancy of related information items (articles, charts, peer profiles, event announcements, news items, etc.) to be recommended to a given user at a given time point. It can also be used to define user clusters to be used in collaborative filtering and other recommendation logic.
[0068] It should now be appreciated that the present invention provides advantageous methods and systems for providing more targeted items and peer recommendations from a recommendation algorithm. In particular, it should be appreciated that the present invention moves away from the limited binary scoring of prior art recommendation engines to a more iterative approach based on a continuum of inputs from the user's interaction with and/or modifications to an item (rather than simply whether an item was used/viewed). Although the invention has been described in connection with various illustrated embodiments, numerous modifications and adaptations may be made thereto without departing from the spirit and scope of the invention as set forth in the claims.