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Web History Content Indexing with Private and Collaborative Expert focused search

IP.com Disclosure Number: IPCOM000239459D
Publication Date: 2014-Nov-10
Document File: 4 page(s) / 76K

Publishing Venue

The IP.com Prior Art Database


A mechanism for improved discovery of information by searching user and expert browsing history is described. Through an efficient indexing scheme and a cloud service a method to efficiently search for relevant content related to a topic is described.

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Web History Content Indexing with Private and Collaborative Expert focused search

Aspects of this idea involve searching for content to clarify understanding or develop new knowledge. When searching we may encounter ideas that marginally interest us at the time, but that later become more interesting to us as our circumstances change or a colleague reports an interest in what we found which is learned of later. Wouldn't it be useful if we could look back to locate those ideas and concepts that we are interested in now or that a colleague has just expressed an interest in? The cumulative effect should allow reloading of data context much faster than now and may improve outcomes, particularly in research and engineering.

    The problem solved is context reloading of discovered information that has a higher value now than anticipated at the time of discovery. This information may be privately held or shared with colleagues. This information may be consulted from various devices (PC, phone, etc), but by the same user.

    The history functionality currently available in common browsers is lacking in functionality allowing for very limited search "page titles only".

    In addition to efficiently finding data that has previously been discovered personally, the ability to discover the topics most relevant to a particular subject based on what the experts are reading is specified.

    This article allows a very efficient "full text" search on personal browser history, and also allows for the searching of the browser history of colleagues and the browser history of experts identified through a known expert search mechanism.

    Presented in this article is the ability to share browsing history within communities or publicly, and the combination of expert search and shared browser history searching to yield and rank the most relevant topics.

    Essentially, each web browser records where the user has been, indexing page URL, page content and title. This indexed store is synchronised between the local workstation and a Cloud Service.

This allows a user (or group of users) to browse for any word or group of

words in their previous consulted Web pages. If the searched word or group of

words was already consulted by the user in the past, a list with the consulted pages is returned to the user.

    This also allows finding the list of experts based on a search on keywords in the history of web pages consulted by people; this is based on the assumption that an expert will consult pages related to their domain of expertise and related to their current projects (that are definitely related to their expertise).

    Filtered research result can be provided by exploiting the fact that the idea stores additional settings characterising the Web search (e.g. time spent on a Web page, number of times the page was accessed, etc), and that are used to filter the returned result.

    Expertise search is a known technology that we leverage as part of this. What is proposed is a system and m...