The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 18, 2022

Filed:

Feb. 27, 2016
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Dong Han Wang, Bellevue, WA (US);

Xiaofei Huang, Beijing, CN;

Jinghua Chen, Redmond, WA (US);

Nanshan Zeng, Bellevue, WA (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 16/2457 (2019.01); G06N 20/00 (2019.01); G06F 16/951 (2019.01);
U.S. Cl.
CPC ...
G06F 16/24578 (2019.01); G06F 16/951 (2019.01); G06N 20/00 (2019.01);
Abstract

Techniques for dynamically generating deeplink search results in response to navigational search queries. In an aspect, to address user search queries, a general-purpose search engine is provided in parallel with a dedicated engine for specifically ranking deeplinks. Upon identifying a received query as a navigational query, a parallel query is generated from a common domain and user query, and provided to the dedicated engine. The engine accesses relevant deeplink URL's from a search index, which may be frequently refreshed and updated with the most recent Web contents. Ranking of deeplink URL's may be performed according to an algorithm that processes query-level features and document-level features of URL's to be ranked. In an aspect, the algorithm may be trained from search engine logs and/or Web browser logs, by calculating a Log-based Normalized Discounted Cumulative Gain (LNDCG) designed to quantify relevance of search results to queries based on user click behavior.


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