US 11,308,097 B2Granted

Method of and server for generating meta-feature for ranking documents

AssigneeYandex Europe AG

InventorsAleksandr Valerievich Safronov, Victor Vitalievich Ploshykhyn, Ivan Ivanovich Belotelov

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Abstract

A method and a server for generating a meta-feature for ranking documents by a machine learning algorithm (MLA). A past query having been previously submitted on a server is acquired, and a set of past documents having been presented as search results in response to the past query is acquired, where each respective document includes a plurality of features, and respective values for the plurality of features. The meta-feature is generated, where a respective value of the meta-feature for a respective document is based on: a respective value of a given feature of the plurality of features for the respective document, and a value of a parameter associated with the set of past documents. The meta-feature is validated based on its usefulness for ranking future search engine results pages (SERPs). The MLA is then trained to generate the meta-feature for ranking documents in response to a new query.

Claims18

Dependent claims

A computer-implemented method for generating a meta-feature for ranking documents by a machine learning algorithm (MLA) executed by a server, the method executable by the server, the method comprising:

acquiring, by the server, an indication of a past query having been submitted on the server;
acquiring, by the server, a set of past documents, the set of past documents having been presented as search results in response to the past query, each past document of the set of past documents including:
a first plurality of features having been used for ranking past documents in the set of past documents, and
respective values for the first plurality of features;
generating, by the server, the meta-feature, a respective value of the meta-feature for a given past document being a relative value between a respective value of a given feature of the first plurality of features for the given past document and at least one other respective value of the given feature associated with other ones of the set of past documents;
validating, by the server, the meta-feature based on a usefulness thereof for ranking future search engine results pages (SERPs),
the usefulness of the meta-feature being determined by comparing, by the processor, user interactions with:
(i) a current ranking of the set of past documents and (ii) a new ranking of the set of past documents, the new ranking being based at least on the meta-feature;
in response to the usefulness of the meta-feature being above a predetermined threshold, generating a plurality of training objects for training the MLA for ranking future SERPs,
a given training object of the plurality of training objects including:
(i) the indication of the past query;
(ii) the given past document of the set of past documents;
(iii) the respective values of the first plurality of features associated therewith;
and (iv) the respective value of the meta-feature associated therewith.

11 more elements

A computer-implemented method for generating a meta-feature for ranking documents by a machine learning algorithm (MLA) executed by a server, the MLA having been trained to generate the meta-feature for ranking the documents in response to a given query, the method executable by the server, the method comprising:

receiving, from an electronic device connected to the server, a new query, the MLA not having been trained to rank documents based at least in part on the meta-feature for the new query;
generating, by the server, a set of current documents relevant to the new query, each current document of the respective set of current documents including a first plurality of features;
generating, by the MLA, the meta-feature, a respective value of the meta-feature for a given current document being a relative value between a respective predicted value of a given feature of the first plurality of features for the given current document and at least one other respective predicted value of the given feature associated with other ones of the set of current documents;
ranking, by the MLA, the set of current documents based at least in part on the first plurality of features and the meta-feature to obtain a respective final ranked list of documents;
and
transmitting, by the server to the electronic device, a respective SERP including the respective final ranked list of documents.

3 more elements

Dependencies are inferred from the claim text.

Facts

Application: 16/504,079Filed 5 Jul 2019
Priority: RU 201814417813 Dec 2018
Published: US 2020/0192904 A118 Jun 2020
Granted: 19 Apr 2022
Term ends: Not estimatedThe source records don’t support an estimate.

Classification7 codes

G06F 16/24578
With adaptation to user needs: using ranking
G06F 16/953
Retrieval from the web: querying, e.g. by the use of web search engines
G06F 16/24539
Query rewriting; Transformation: using cached or materialised query results
G06F 16/3349
Query processing: reuse of stored results of previous queries

Family

US 2020/0192904 A1Pre-grant publication · published 18 Jun 2020
US 11,308,097 B2This patent

From the US filing history. Foreign family members aren’t listed.

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