International Business Machines Corporation

Alexander Wolcott Holt

Michael E Moran

Barton Wayne Emanuel

Srinivas Varma Chitiveli

Stephen Carl Gates

Jeffrey S Schaffer

Pat Velderman

Robert J Torres

Douglas Stuart Brown

James Robert Rudd

Carlos A Hoyos

Carl Shawn Kessler

A system and method for generating content rules for a Web application server. A system is provided that includes a content manager for selecting a content item; and a segment manager for defining a data segment to associate with a selected content item, wherein the segment manager includes a multifaceted search interface for defining the data segment.

System and method for generating content rules for a website

A system, method and program product for that utilizes user feedback as a boosting mechanism for closed loop content space search processes, such as site-specific web search engines. A search engine is disclosed that includes: a system for searching a database of content items such as web pages; a data collection system for collecting user feedback from users viewing displayed content items regarding information appearing in said displayed content items; a scoring system for assigning a score to content items from the database based on the user feedback; and a system for ranking a set of search results based on the score assigned to content items in the set of search results.

User feedback for search engine boosting

Personalization of content of a web site for a user based on a web site that a user arrives from is disclosed. For example, the content of the web site from which the user arrives (i.e., the originating page), as well as the content of the web page the user has arrived to (i.e., the target page), may be categorized as pertaining to particular subjects or topics. Any time a user comes from an originating page, the subject categories for the originating page and the target page may be compared to determine if like categories exist between the pages. In the event that like categories are found, the target page may be personalized based on those categories.

Referrer-based website personalization

Systems, methods and articles of manufacture are disclosed for identifying a training document for a content classifier. One or more thresholds may be defined for designating a document as a training document for a content classifier. A plurality of documents may be evaluated to compute a score for each respective document. The score may represent suitability of a document for training the content classifier with respect to a category. The score may be computed based on content of the plurality of documents, metadata of the plurality of documents, link structure of the plurality of documents, user feedback (e.g., user supplied document tags) received for the plurality of documents, and document metrics received for the plurality of documents. Based on the computed scores, a training document may be selected. The content classifier may be trained using the selected training document.

Identifying training documents for a content classifier

The Facet Navigator permits users to set custom constraints for searching databases by facet, displays facets representing fields in a database, and provides a manipulator for each facet. The manipulator may be a slider bar, or a drop-down menu, or some other interactive device known to persons skilled in the art. When a user sets constraints for a facet with the manipulator, the Facet Navigator searches the database based on the constraints and displays a list of items in the database that satisfy the constraints. The Facet Navigator displays a preview of interim results whenever a cursor is moved over an active region of the manipulator, where the preview includes details of database items meeting a search criteria based on the location of the cursor on the manipulator.

Custom constraints for faceted exploration

Systems, methods and articles of manufacture are disclosed for detecting a duplicate document. A plurality of documents may be assigned to categories, each category corresponding to a collection of duplicates, or near duplicate documents. A new document may be received. The new document may be evaluated against each category to determine a similarity score between the new document and each category. The new document may be identified as a duplicate based on the similarity scores and thresholds for each category. An action may then be performed on the duplicate based on duplication rules. The thresholds and duplication rules may be customized by a user.

Detecting duplicate documents using classification

Systems, methods and articles of manufacture are disclosed for generating search results based on user feedback. A request may be received to generate search results retrieved using a search string. The request may include user feedback for one or more selected documents of the search results. Improved search results may be generated based on the search results and the feedback for one or more selected documents of the search results. The improved search results may be output to a graphical display device.

Generating search results based on user feedback

Classifying electronic mail (e-mail) based on content and predefined categories. Content of a received e-mail may be analyzed to determine one of a plurality of predefined categories into which the e-mail is classified. A relevancy score may also be calculated to indicate the strength of correlation between the e-mail and the category. A user may be allowed to sort e-mails in an e-mail box based on the category names and/or relevancy scores.

Classification of electronic messages based on content

A system and computer readable medium for providing a set of refinement categories for a set of search results generated in response to a search query. The system comprises: a category identifier system that analyzes each search result and identifies at least one category from a hierarchy of categories for each search result, thereby providing a list of identified categories; a ranking system that ranks each category in the list of identified categories; and a selection system that selects a predetermined number of the highest ranking categories from the list of identified categories to generate the set of refinement categories, wherein the selection system eliminates categories from the set of refinement categories if the category has a parent in the set of refinement categories.

System and computer readable medium for generating refinement categories for a set of search results

A system for enhancing search results generated in response to a search query. The system comprises: a category identifier system that analyzes each search result and identifies at least one category from a hierarchy of categories for each search result, thereby providing a list of identified categories; a ranking system that ranks each category in the list of identified categories; and a selection system that selects a predetermined number of the highest ranking categories from the list of identified categories to generate the set of refinement categories, wherein the selection system eliminates categories from the set of refinement categories if the category has a parent in the set of refinement categories.

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New Paltz, NY, United States of America

Alexander Wolcott Holt