Method and apparatus for identifying, extracting, capturing, and leveraging expertise and knowledge
First Claim
1. A computer-implemented method for automatically determining within an on-line community the topic/context of each on-line asset, in which an affinity engine, comprising a processor, executes the steps of:
- observing usage patterns by a community associated with said asset;
employing automatic techniques to extract patterns from said usage;
identifying usefulness of an online asset by observing user implicit behaviors in connection with said usage patterns of said online asset and by extracting behavioral patterns from said observations;
refining said identified online asset usefulness by context, wherein the context of each onlineasset is automatically detected based on observed terms/topics from individual and group user behaviors when said online asset is determined to be useful based upon said individual and group user behaviors;
assigning to every term and phrase a term vector entry for said asset that describes a degree to which an identified asset topic has an affinity with each said term and phrase, given the observed usage patterns;
refining a rating of said term vector entry based on learned associations between assets derived from community navigation and usage patterns;
using said term vector entry ratings for any of;
determining and describing a topic of said asset;
determining and describing inherent relationships between topics;
determining and describing inherent relationships between assets;
determining and describing a current interest of a user;
determining and describing similarity between a user'"'"'s current interest and each asset;
said observed usage patterns comprising user online search, navigation, and interaction behavior, said behavior including any of searches performed and position in user trail, assets viewed and position in user trail, dwell, range, scrolling, think time, and mouse movement on an asset, anchors and lines used in asset text, virtual bookmarks and virtual printing, and explicit downloading, emailing, printing, saving, and removing to and/or from a computer hardware memory.
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Accused Products
Abstract
The invention comprises a set of complementary techniques that dramatically improve enterprise search and navigation results. The core of the invention is an expertise or knowledge index, called UseRank that tracks the behavior of website visitors. The expertise-index is designed to focus on the four key discoveries of enterprise attributes: Subject Authority, Work Patterns, Content Freshness, and Group Know-how. The invention produces useful, timely, cross-application, expertise-based search and navigation results. In contrast, traditional Information Retrieval technologies such as inverted index, NLP, or taxonomy tackle the same problem with an opposite set of attributes than what the enterprise needs: Content Population, Word Patterns, Content Existence, and Statistical Trends. Overall, the invention emcompasses Baynote Search—a enhancement over existing IR searches, Baynote Guide—a set of community-driven navigations, and Baynote Insights—aggregated views of visitor interests and trends and content gaps.
120 Citations
30 Claims
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1. A computer-implemented method for automatically determining within an on-line community the topic/context of each on-line asset, in which an affinity engine, comprising a processor, executes the steps of:
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observing usage patterns by a community associated with said asset; employing automatic techniques to extract patterns from said usage; identifying usefulness of an online asset by observing user implicit behaviors in connection with said usage patterns of said online asset and by extracting behavioral patterns from said observations; refining said identified online asset usefulness by context, wherein the context of each online asset is automatically detected based on observed terms/topics from individual and group user behaviors when said online asset is determined to be useful based upon said individual and group user behaviors; assigning to every term and phrase a term vector entry for said asset that describes a degree to which an identified asset topic has an affinity with each said term and phrase, given the observed usage patterns; refining a rating of said term vector entry based on learned associations between assets derived from community navigation and usage patterns; using said term vector entry ratings for any of; determining and describing a topic of said asset; determining and describing inherent relationships between topics; determining and describing inherent relationships between assets; determining and describing a current interest of a user; determining and describing similarity between a user'"'"'s current interest and each asset; said observed usage patterns comprising user online search, navigation, and interaction behavior, said behavior including any of searches performed and position in user trail, assets viewed and position in user trail, dwell, range, scrolling, think time, and mouse movement on an asset, anchors and lines used in asset text, virtual bookmarks and virtual printing, and explicit downloading, emailing, printing, saving, and removing to and/or from a computer hardware memory. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
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16. An affinity engine for automatically determining within an on-line community the topic/context of each on-line asset, comprising:
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a processor for observing usage patterns by a community associated with said asset; said processor employing automatic techniques to extract patterns from said usage; said processor identifying usefulness of an online asset by observing user implicit behaviors in connection with said usage patterns of said online asset and by extracting behavioral patterns from said observations; said processor refining said identified online asset usefulness by context, wherein the context of each online asset is automatically detected based on observed terms/topics from individual and group user behaviors when said online asset is determined to be useful based upon said individual and group user behaviors; said processor assigning to every term and phrase a term vector entry for said asset that describes a degree to which an identified asset topic has an affinity with each said term and phrase, given the observed usage patterns; said processor refining a rating of said term vector entry based on learned associations between assets derived from community navigation and usage patterns; said processor using said term vector entry ratings for any of; determining and describing a topic of said asset; determining and describing inherent relationships between topics; determining and describing inherent relationships between assets; determining and describing a current interest of a user; determining and describing similarity between a user'"'"'s current interest and each asset; said observed usage patterns comprising user online search, navigation, and interaction behavior, said behavior including any of searches performed and position in user trail, assets viewed and position in user trail, dwell, range, scrolling, think time, and mouse movement on an asset, anchors and lines used in asset text, virtual bookmarks and virtual printing, and explicit downloading, emailing, printing, saving, and removing. - View Dependent Claims (17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30)
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Specification