Context-sensitive content recommendation using enterprise search and public search

Abstract

Architecture that recommends (suggests) personalized and relevant documents from internal networks and / or public networks (search engines) to help the user complete / update a document currently being worked. The architecture extracts the query and uses the context to perform the search, and performs the search from within the editing application, using the entire text of the document to improve relevance. User context and textual / session context are employed to search for relevant documents. Relevant documents are proactively recommended when the user is authoring the document within an authoring application. The search operation is performed reactively using authoring context (e.g., user, textual, session, etc.) in authoring applications. Results are recommended from both internal documents (e.g., local storage, corporate network, etc.) and public documents (e.g., using a public search engine). Moreover, a deep neural network (DNN) can be utilized to re rank the documents using both personalized features and context sensitive and / or context-free features.

Description

Background technique [0001] Considering the ever-increasing amount of data being created and stored, it is accordingly increasingly important to provide search techniques that can search large amounts of data efficiently and in a reasonable amount of time. Searches generally involve web content; however, such generic and slow searches do not satisfy the more focused and useful searches that users currently need. [0002] Existing solutions require users to formulate their own queries, leave the document they are editing and use a browser to search and find results using only a few keywords entered, which is insufficient or inefficient in many cases of. Contents of the invention [0003] A simplified summary is presented below in order to provide a basic understanding of some of the novel implementations described herein. This summary is not an extensive overview and it does not intend to identify key / critical elements or to delineate the scope thereof. Its sole purpose is...

AI Technical Summary

Problems solved by technology

Searches typically involve web content; however, such generic and slow searches fall short of the more focused and useful searches that users currently need

[0002] Existing solutions require users to formulate their own queries, leave the document they are editing and use a browser to search and find results using only a few keywords entered, which is insufficient or inefficient in many cases of

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