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US 9,310,879 B2Granted
Methods and systems for displaying web pages based on a user-specific browser history analysis
AssigneeXerox Corporation
InventorRobert J. St. Jacques, Jr.
Life of this patent
Estimating the term…
Abstract
Methods and systems for automatically parsing the content of a user's browser history to extract information about that user's browsing habits, interests, likes, and dislikes utilizing text analytics and unsupervised machine learning. A topic model can be utilized to filter the display of web content and employ visualization techniques to highlight specific content (e.g. keywords) that correspond with the users specific tastes. The analysis can be as coarse or fine as the user desires and all of the analysis can be done locally on the user's own data processing device.
Claims18
A method for displaying user specific content, said method comprising:
- determining a size of a random sample of a plurality of links in a browser history;
- selecting a predetermined number of links from said plurality of links in said browser history for said random sample of said plurality of links;
- fetching content for each of said plurality of links in said random sample;
- extracting a plurality of topics comprising a variable number of topics from said content including text from HTML, said extracting of said plurality of topics executed in a background as a low priority process;
- generating a topic model from said plurality of topics extracted from said content, said topic model to be used to alter a manner in which selected web content is displayed;
- evaluating content of a newly selected web page against said topic model after generating said topic model to determine a probability score for each of said plurality of topics based on how accurately each of said plurality of topics describes said content of the newly selected web page and by providing every topic in said topic model with said probability score within a certain threshold of all other topics;
- selecting a subset of said plurality of topics based on said probability score;
- evaluating said content from said newly selected web page for keywords associated with said subset of topics and which represent significant trends across said subset of tonics;
- and
- highlighting said keywords within said newly selected web page based on said topic model in order to display user specific content.
7 more elements
A computer-readable non-transitory storage media comprising instructions operable for displaying user specific content to cause a computer to:
- determine a size of a random sample of a plurality of links in a browser history;
- select a predetermined number of links from said plurality of links in said browser history for said random sample of said plurality of links;
- fetch content for each of said plurality of links in said random sample;
- extract a plurality of topics comprising a variable number of topics from said content including text from HTML, said extracting of said plurality of topics executed in a background as a low priority process;
- generate a topic model from said plurality of topics extracted from said content, said topic model to be used to alter a manner in which selected web content is displayed;
- evaluate content of a newly selected web page against said topic model after generating said topic model to determine a probability score for each of said plurality of topics based on how accurately each of said plurality of topics describes said content of the newly selected web page and by providing every topic in said topic model with said probability score within a certain threshold of all other topics;
- select a subset of said plurality of topics based on said probability score;
- evaluate said content from said newly selected web page for keywords associated with said subset of topics and which represent significant trends across said subset of topics;
- and
- highlight said keywords within said newly selected web page based on said topic model in order to display user specific content.
7 more elements
A system for displaying user specific content, said system comprising:
- a processor;
- and
- a non-transitory computer-usable medium embodying computer program code, said non-transitory computer-usable medium capable of communicating with the processor, said computer program code comprising instructions executable by said processor and configured for:
- determining a size of a random sample of a plurality of links in a browser history;
- selecting a predetermined number of links from said plurality of links in said browser history for said random sample of said plurality of links;
- fetching content for each of said plurality of links in said random sample;
- extracting a plurality of topics comprising a variable number of topics from said content including text from HTML, said extracting of said plurality of topics executed in a background as a low priority process;
- generating a topic model from said plurality of topics extracted from said content, said topic model to be used to alter a manner in which selected web content is displayed;
- evaluating content of a newly selected web page against said topic model after generating said topic model to determine a probability score for each of said plurality of topics based on how accurately each of said plurality of topics describes said content of the newly selected web page and by providing every topic in said topic model with said probability score within a certain threshold of all other topics;
- selecting a subset of said plurality of topics based on said probability score;
- evaluating said content from said newly selected web page for keywords associated with said subset of topics and which represent significant trends across said subset of topics;
- and
- highlighting said keywords within said newly selected web page based on said topic model in order to display user specific content.
10 more elements
Dependencies are inferred from the claim text.