Google Inc.

Alexandru Marius Pasca

Peter Szabolcs Dienes

Lev Finkelstein

Benjamin Van Durme

Jay Yagnik

Yushi Jing

Hrishikesh Balkrishna Aradhye

George Dan Toderici

Luciano Sbaiz

Dekang Lin

Wei Cai

Artiom Myaskouvskey

Razvan Constantin Bunescu

Named entities are disambiguated in search queries and other contexts using a disambiguation scoring model. The scoring model is developed using a knowledge base of articles, including articles about named entities. Various aspects of the knowledge base, including article titles, redirect pages, disambiguation pages, hyperlinks, and categories, are used to develop the scoring model.

Disambiguation of named entities

Methods, systems, and apparatus, including computer program products, for extracting information from unstructured text. Fact pairs are used to extract basic patterns from a body of text. Patterns are generalized by replacing words with classes of similar words. Generalized patterns are used to extract further fact pairs from the body of text. The process can begin with fact pairs, basic patterns, or generalized patterns.

Extracting information from unstructured text using generalized extraction patterns

Technology is described herein for creating new, inferred queries that are suitable for use as query suggestions. The technology includes mapping different past queries that represent different information requests, but that share a number of terms having the same or similar form. An inferred query is created by replacing unshared terms in one mapped query with the unshared terms in another mapped query, based on the similarity between the unshared terms in the two mapped queries. The inferred query thus represents a new information request that is derived from the information requests of the past queries used to form it. The inferred query can then be provided as a query suggestion, which increases the likelihood of providing query suggestions that will assist users in finding the information they seek. In doing so, meaningful query suggestions can be provided to users seeking information outside the coverage of the past queries.

Creation of inferred queries for use as query suggestions

A plurality of images related to a particular image are determined, and a plurality of annotations associated with the plurality of images are identified. An ontology is determined based on the plurality of annotations, and an image annotation for the particular image is determined based on the ontology. The ontology may be a semantic ontology, for example.

System and method for determining an annotation for an image

Methods and apparatus related to processing of at least one descriptive term of a query to obtain at least one query suggestion for a query. A descriptive term may be identified in a partial search query. A modified partial query suggestion request for the partial search query may be transmitted that omits the descriptive term. At least one query suggestion result for the modified partial query suggestion request may be received and the descriptive term reinserted into the query suggestion result.

Creating query suggestions based on processing of descriptive term in a partial query

A classifier training system learns classifiers for categories by combining data from a category-instance repository comprising relationships between categories and more specific instances of those categories with a set of video classifiers for different concepts. The category-instance repository is derived from the domain of textual documents, such as web pages, and the concept classifiers are derived from the domain of video. Taken together, the category-instance repository and the concept classifiers provide sufficient data for obtaining accurate classifiers for categories that encompass other lower-level concepts, where the categories and their classifiers may not be obtainable solely from the video domain.

Learning category classifiers for a video corpus

Systems, techniques, and machine-readable instructions for inferring attributes from search queries. In one aspect, a method includes receiving a description of a collection of search queries, inferring attributes of entities from the description of the collection of search queries, associating the inferred attributes with identifiers of entities characterized by the attributes, and making the associations of the attributes and entities available.

Inferring attributes from search queries

Methods and systems for retrieval of information items and associated sentence fragments are described. One method described comprises identifying at least a first entry in an index relevant to a search query, wherein the first entry comprises a first information item and a first associated sentence fragment, and wherein the index comprises a plurality of information items and associated sentence fragments, and generating a search result set relevant to the search query comprising at least the first information item.

Methods and systems for retrieval of information items and associated sentence fragments

Methods and systems for identification of paraphrases from an index of information items and associated sentence fragments are described. One method described comprises identifying a pair of sentence fragments each having a same associated information item from an index, wherein the index comprises a plurality of information items and associated sentence fragments, and identifying a paraphrase pair from the pair of sentence fragments.

Methods and systems for identifying paraphrases from an index of information items and associated sentence fragments

Methods and apparatus, including systems and computer program products, to acquire potential paraphrases from textual input. In one aspect, textual input is received, a first map is generated, where the key of the first map is an ngram identified in the textual input and the value associated with the key of the first map is a unique identifier, a second map is generated, where the key of the second map is an anchor identified from the ngram and the value associated with the key of the second map is one or more middle portions associated with the anchor, and a third map is generated, where the key of the third map is a potential paraphrase pair identified from the middle portions and the value associated with the key of the third map is the one or more unique anchors associated with the potential paraphrase pair.

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Sunnyvale, CA, United States of America

Alexandru Marius Pasca