Patents by Inventor Massimiliano Ciaramita
Massimiliano Ciaramita has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20230281193Abstract: Systems, methods, and computer readable media related to generating query variants for a submitted query. In many implementations, the query variants are generated utilizing a generative model. A generative model is productive, in that it can be utilized to actively generate a variant of a query based on application of tokens of the query to the generative model, and optionally based on application of additional input features to the generative model.Type: ApplicationFiled: May 12, 2023Publication date: September 7, 2023Inventors: Jyrki Alakuijala, Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Wojciech Gajewski, Andrea Gesmundo, Neil Houlsby, Wei Wang
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Patent number: 11663201Abstract: Systems, methods, and computer readable media related to generating query variants for a submitted query. In many implementations, the query variants are generated utilizing a generative model. A generative model is productive, in that it can be utilized to actively generate a variant of a query based on application of tokens of the query to the generative model, and optionally based on application of additional input features to the generative model.Type: GrantFiled: April 27, 2018Date of Patent: May 30, 2023Assignee: GOOGLE LLCInventors: Jyrki Alakuijala, Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Wojciech Gajewski, Andrea Gesmundo, Neil Houlsby, Wei Wang
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Patent number: 10783156Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for scoring candidate answer passages. In one aspect, a method includes receiving a query determined to be a question query that seeks an answer response and data identifying resources determined to be responsive to the query; for a subset of the resources: receiving candidate answer passages; determining, for each candidate answer passage, a query term match score that is a measure of similarity of the query terms to the candidate answer passage; determining, for each candidate answer passage, an answer term match score that is a measure of similarity of answer terms to the candidate answer passage; determining, for each candidate answer passage, a query dependent score based on the query term match score and the answer term match score; and generating an answer score that is a based on the query dependent score.Type: GrantFiled: February 22, 2018Date of Patent: September 22, 2020Assignee: Google LLCInventors: Steven D. Baker, Srinivasan Venkatachary, Robert Andrew Brennan, Per Bjornsson, Yi Liu, Hadar Shemtov, Massimiliano Ciaramita, Ioannis Tsochantaridis
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Publication number: 20200142888Abstract: Systems, methods, and computer readable media related to generating query variants for a submitted query. In many implementations, the query variants are generated utilizing a generative model. A generative model is productive, in that it can be utilized to actively generate a variant of a query based on application of tokens of the query to the generative model, and optionally based on application of additional input features to the generative model.Type: ApplicationFiled: April 27, 2018Publication date: May 7, 2020Inventors: Jyrki Alakuijala, Christian Buck, Jannis Bulian, Massimiliano Ciaramita, Wojciech Gajewski, Andrea Gesmundo, Neil Houlsby, Wei Wang
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Patent number: 9940367Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for scoring candidate answer passages. In one aspect, a method includes receiving a query determined to be a question query that seeks an answer response and data identifying resources determined to be responsive to the query; for a subset of the resources: receiving candidate answer passages; determining, for each candidate answer passage, a query term match score that is a measure of similarity of the query terms to the candidate answer passage; determining, for each candidate answer passage, an answer term match score that is a measure of similarity of answer terms to the candidate answer passage; determining, for each candidate answer passage, a query dependent score based on the query term match score and the answer term match score; and generating an answer score that is a based on the query dependent score.Type: GrantFiled: August 12, 2015Date of Patent: April 10, 2018Assignee: Google LLCInventors: Steven D. Baker, Srinivasan Venkatachary, Robert Andrew Brennan, Per Bjornsson, Yi Liu, Hadar Shemtov, Massimiliano Ciaramita, Ioannis Tsochantaridis
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Patent number: 9881077Abstract: News documents from one or more sources are aggregated. The news documents are grouped into a plurality of news collections. Each of the news collections includes a sub-set of the news documents having related content. Objects described by the news collections are determined. The objects collectively form a set of objects. A relevance of each of the news collections is measured with respect to the objects respectively described by the news collections and one or more news collections are determined from the plurality of news collections to be associated with a first object included in the set of objects based on the relevance of the one or more news collections to the first object.Type: GrantFiled: August 8, 2013Date of Patent: January 30, 2018Assignee: Google LLCInventors: Enrique Alfonseca, Yasemin Altun, Massimiliano Ciaramita, Jean-Yves Delort, Ekaterina Filippova, Thomas Hofmann, Evangelos Kanoulas, Ioannis Tsochantaridis
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Patent number: 9251206Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a generalized edit distance for queries. In one aspect, a method includes selecting query pairs of consecutive queries, each query pair being a first query and a second query consecutively submitted as separate queries, each first and second query including at least one term. For each query pair, the method includes selecting term pairs from the query pair, each term pair being a first term in the first query and a second term in the second query; and determining a co-occurrence value for each term pair. The method also includes determining transition costs based on the co-occurrence values for term pairs, each transition cost indicative of a cost of transitioning from a first term in a first query to a second term in a second query consecutive to the first query.Type: GrantFiled: April 3, 2013Date of Patent: February 2, 2016Assignee: Google Inc.Inventors: Massimiliano Ciaramita, Amac Herdagdelen, Daniel Mahler
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Patent number: 8918328Abstract: A system for and method for ranking results. The system includes a server configured to receive a query and an advertisement engine configured to receive the query from the server. The advertisement engine ranks advertisements based on various features, including at least one word overlap feature and a correlation feature.Type: GrantFiled: April 18, 2008Date of Patent: December 23, 2014Assignee: Yahoo! Inc.Inventors: Vassilis Plachouras, Vanessa Murdock, Massimiliano Ciaramita
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Patent number: 8825571Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining query suggestions from multiple correlation measures. In one aspect, a method includes receiving a first query and second queries, each of the first and second queries including one or more terms; for each second query and a linear model, receiving correlation scores measuring the correlation between the first query and the respective second query, each correlation score received from a respective correlation process, and each respective correlation process being different from the other respective correlation processes, and applying the linear model to the plurality of correlation scores to determine a combined correlation score that quantifies a combined correlation between the first query and the respective second query based on the plurality of correlation scores. The second queries are ranked in an order according to their respective combined correlations scores.Type: GrantFiled: June 4, 2013Date of Patent: September 2, 2014Assignee: Google Inc.Inventors: Enrique Alfonseca, Massimiliano Ciaramita, Keith B. Hall
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Publication number: 20130226950Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a generalized edit distance for queries. In one aspect, a method includes selecting query pairs of consecutive queries, each query pair being a first query and a second query consecutively submitted as separate queries, each first and second query including at least one term. For each query pair, the method includes selecting term pairs from the query pair, each term pair being a first term in the first query and a second term in the second query; and determining a co-occurrence value for each term pair. The method also includes determining transition costs based on the co-occurrence values for term pairs, each transition cost indicative of a cost of transitioning from a first term in a first query to a second term in a second query consecutive to the first query.Type: ApplicationFiled: April 3, 2013Publication date: August 29, 2013Inventors: Massimiliano Ciaramita, Amac Herdagdelen, Daniel Mahler
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Patent number: 8478699Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining query suggestions from multiple correlation measures. In one aspect, a method includes receiving a first query and second queries, each of the first and second queries including one or more terms; for each second query and a linear model, receiving correlation scores measuring the correlation between the first query and the respective second query, each correlation score received from a respective correlation process, and each respective correlation process being different from the other respective correlation processes, and applying the linear model to the plurality of correlation scores to determine a combined correlation score that quantifies a combined correlation between the first query and the respective second query based on the plurality of correlation scores. The second queries are ranked in an order according to their respective combined correlations scores.Type: GrantFiled: April 30, 2010Date of Patent: July 2, 2013Assignee: Google Inc.Inventors: Enrique Alfonseca, Massimiliano Ciaramita, Keith B. Hall
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Patent number: 8417692Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a generalized edit distance for queries. In one aspect, a method includes selecting query pairs of consecutive queries, each query pair being a first query and a second query consecutively submitted as separate queries, each first and second query including at least one term. For each query pair, the method includes selecting term pairs from the query pair, each term pair being a first term in the first query and a second term in the second query; and determining a co-occurrence value for each term pair. The method also includes determining transition costs based on the co-occurrence values for term pairs, each transition cost indicative of a cost of transitioning from a first term in a first query to a second term in a second query consecutive to the first query.Type: GrantFiled: May 18, 2011Date of Patent: April 9, 2013Assignee: Google Inc.Inventors: Massimiliano Ciaramita, Amac Herdagdelen, Daniel Mahler
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Publication number: 20120109758Abstract: A system for selecting electronic advertisements from an advertisement pool to match the surrounding content is disclosed. To select advertisements, the system takes an approach to content match that focuses on capturing subtler linguistic associations between the surrounding content and the content of the advertisement. The system of the present invention implements this goal by means of simple and efficient semantic association measures dealing with lexical collocations such as conventional multi-word expressions like “big brother” or “strong tea”. The semantic association measures are used as features for training a machine learning model. In one embodiment, a ranking SVM (Support Vector Machines) trained to identify advertisements relevant to a particular context. The trained machine learning model can then be used to rank advertisements for a particular context by supplying the machine learning model with the semantic association measures for the advertisements and the surrounding context.Type: ApplicationFiled: October 24, 2011Publication date: May 3, 2012Inventors: Vanessa Murdock, Vassilis Plachouras, Massimiliano Ciaramita
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Patent number: 8156053Abstract: An automated technique for tagging documents includes using a semantic tagger to generate an annotation that associates a standard tag with a first text fragment of the user-defined document, wherein the tagger is trained on a standard document annotated with a standard tag, associating the first user-defined tag with a second text fragment of the user-defined document in response to the second text fragment matching a value associated with the first user-defined tag, and establishing a mapping between the standard tag and the first user-defined tag in response to existence of a requisite correlation between the standard tag and the user-defined tag. The technique may further include selecting from the user-defined document a tagged text fragment that is associated with a second user-defined tag, and providing the tagged text fragment and a standard tag associated by the mapping with the second user-defined tag to the tagger as additional training input.Type: GrantFiled: May 9, 2008Date of Patent: April 10, 2012Assignee: Yahoo! Inc.Inventors: Peter Mika, Hugo Zaragoza, Massimiliano Ciaramita, Jordi Atserias
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Patent number: 8145649Abstract: A system for selecting electronic advertisements from an advertisement pool to match the surrounding content is disclosed. To select advertisements, the system takes an approach to content match that takes advantage of machine translation technologies. The system of the present invention implements this goal by means of simple and efficient machine translation features that are extracted from the surrounding context to match with the pool of potential advertisements. Machine translation features used as features for training a machine learning model. In one embodiment, a ranking SVM (Support Vector Machines) trained to identify advertisements relevant to a particular context. The trained machine learning model can then be used to rank advertisements for a particular context by supplying the machine learning model with the machine translation features measures for the advertisements and the surrounding context.Type: GrantFiled: December 16, 2010Date of Patent: March 27, 2012Assignee: Yahoo! Inc.Inventors: Vanessa Murdock, Massimiliano Ciaramita, Vassilis Plachouras
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Patent number: 8073803Abstract: A system for selecting electronic advertisements from an advertisement pool to match the surrounding content is disclosed. To select advertisements, the system takes an approach to content match that focuses on capturing subtler linguistic associations between the surrounding content and the content of the advertisement. The system of the present invention implements this goal by means of simple and efficient semantic association measures dealing with lexical collocations such as conventional multi-word expressions like “big brother” or “strong tea”. The semantic association measures are used as features for training a machine learning model. In one embodiment, a ranking SVM (Support Vector Machines) trained to identify advertisements relevant to a particular context. The trained machine learning model can then be used to rank advertisements for a particular context by supplying the machine learning model with the semantic association measures for the advertisements and the surrounding context.Type: GrantFiled: July 16, 2007Date of Patent: December 6, 2011Assignee: Yahoo! Inc.Inventors: Vanessa Murdock, Vassilis Plachouras, Massimiliano Ciaramita
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Publication number: 20110295840Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a generalized edit distance for queries. In one aspect, a method includes selecting query pairs of consecutive queries, each query pair being a first query and a second query consecutively submitted as separate queries, each first and second query including at least one term. For each query pair, the method includes selecting term pairs from the query pair, each term pair being a first term in the first query and a second term in the second query; and determining a co-occurrence value for each term pair. The method also includes determining transition costs based on the co-occurrence values for term pairs, each transition cost indicative of a cost of transitioning from a first term in a first query to a second term in a second query consecutive to the first query.Type: ApplicationFiled: May 18, 2011Publication date: December 1, 2011Applicant: GOOGLE INC.Inventors: Massimiliano Ciaramita, Amac Herdagdelen, Daniel Mahler
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Publication number: 20110087680Abstract: A system for selecting electronic advertisements from an advertisement pool to match the surrounding content is disclosed. To select advertisements, the system takes an approach to content match that takes advantage of machine translation technologies. The system of the present invention implements this goal by means of simple and efficient machine translation features that are extracted from the surrounding context to match with the pool of potential advertisements. Machine translation features used as features for training a machine learning model. In one embodiment, a ranking SVM (Support Vector Machines) trained to identify advertisements relevant to a particular context. The trained machine learning model can then be used to rank advertisements for a particular context by supplying the machine learning model with the machine translation features measures for the advertisements and the surrounding context.Type: ApplicationFiled: December 16, 2010Publication date: April 14, 2011Inventors: Vanessa Murdock, Massimiliano Ciaramita, Vassilis Plachouras
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Patent number: 7912843Abstract: A system for selecting electronic advertisements from an advertisement pool to match the surrounding content is disclosed. To select advertisements, the system takes an approach to content match that takes advantage of machine translation technologies. The system of the present invention implements this goal by means of simple and efficient machine translation features that are extracted from the surrounding context to match with the pool of potential advertisements. Machine translation features used as features for training a machine learning model. In one embodiment, a ranking SVM (Support Vector Machines) trained to identify advertisements relevant to a particular context. The trained machine learning model can then be used to rank advertisements for a particular context by supplying the machine learning model with the machine translation features measures for the advertisements and the surrounding context.Type: GrantFiled: October 29, 2007Date of Patent: March 22, 2011Assignee: Yahoo! Inc.Inventors: Vanessa Murdock, Massimiliano Ciaramita, Vassilis Plachouras
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Publication number: 20100010895Abstract: A predictor for determining a degree of relevance between a query rewrite and a search query is provided. The predictor may receive a search query from a user via a terminal and identify a set of candidate query rewrites associated with the search query. The predictor may then extract a set of features from advertisements associated with the query rewrites and the search query and determine a degree of relevance between the advertisements and the search query based on a prediction model. The predictor may then determine the degree of relevance between the rewrites and the search query based on the determined degree of relevance between the advertisements and the search query.Type: ApplicationFiled: July 8, 2008Publication date: January 14, 2010Applicant: Yahoo! Inc.Inventors: Evgeniy Gabrilovich, Donald Metzler, Vanja Josifovski, Andrei Broder, Vassilis Plachouras, Vanessa Murdock, Massimiliano Ciaramita