Patents by Inventor Noam Slonim
Noam Slonim 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: 20240028913Abstract: An example system includes a processor to receive unlabeled data, few-shot training data, and a pre-trained model. The processor can split the unlabeled data into a number of groups corresponding to different perspectives. The processor can generate weakly labeled data for each of the number of groups using a respective associated heuristic. The processor can inter-train a model for each different perspective based on respective weakly labeled data. The processor can fine-tune each inter-trained model based on the few-shot training data for each different perspective to generate a final model for each different perspective.Type: ApplicationFiled: July 21, 2022Publication date: January 25, 2024Inventors: Benjamin SZNAJDER, Noam SLONIM, Eyal SHNARCH, Guy LEV, Sachindra JOSHI, Chulaka GUNASEKARA
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Patent number: 11651161Abstract: Automated detection of reasoning in arguments. A training set is generated by: obtaining multiple arguments, each comprising one or more sentences provided as digital text; automatically estimating a probability that each of the arguments includes reasoning, wherein the estimating comprises applying a contextual language model to each of the arguments; automatically labeling as positive examples those of the arguments which have a relatively high probability to include reasoning; and automatically labeling as negative examples those of the arguments which have a relatively low probability to include reasoning. Based on the generated training set, a machine learning classifier is automatically trained to estimate a probability that a new argument includes reasoning. The trained machine learning classifier is applied to the new argument, to estimate a probability that the new argument includes reasoning.Type: GrantFiled: February 13, 2020Date of Patent: May 16, 2023Assignee: International Business Machines CorporationInventors: Avishai Gretz, Edo Cohen-Karlik, Noam Slonim, Assaf Toledo
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Publication number: 20230078698Abstract: An example system includes a processor to pre-train a transformer-based language model on a general domain. The processor can inter-train the pre-trained transformer-based language model using partitioning and classification to generate an inter-trained transformer-based pre-trained language model. The processor can then fine-tune the inter-trained transformer-based pre-trained language model on a target task to generate a fine-tuned transformer-based language model.Type: ApplicationFiled: September 14, 2021Publication date: March 16, 2023Inventors: Eyal SHNARCH, Ariel GERA, Alon HALFON, Lena DANKIN, Leshem CHOSHEN, Ranit AHARONOV, Noam SLONIM
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Publication number: 20220343073Abstract: A computing system, computer program product, and computer-implemented method for quantitative comment summarization are provided. The method includes receiving a collection of comments, identifying a set of candidate key points corresponding to the collection of comments, and selecting a subset of key points from the set of candidate key points, wherein the selected subset of key points includes key points that are most salient in the collection of comments. The method also includes automatically mapping each comment within the collection of comments to any corresponding key points within the subset of key points based on a match score between each comment and key point pair, as well as generating a summary including the subset of key points and an absolute number or percentage of the comments mapped to each key point.Type: ApplicationFiled: April 26, 2021Publication date: October 27, 2022Inventors: Roy BAR-HAIM, Lilach EDEN, Yoav KANTOR, Noam SLONIM
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Patent number: 11403325Abstract: Embodiments may provide techniques for clustering using predefined anchors that take into account the knowledge about the anchors. For example, a method of clustering processing may be implemented in a computer comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor, the method comprising: receiving a plurality of points of data to be clustered and a plurality of predefined anchor data points and clustering the plurality of points of data and at least a subset of the predefined anchor data points. Further, the method may include creating a similarity function where anchor points pull stronger than regular points, such that they function as attractors.Type: GrantFiled: May 12, 2020Date of Patent: August 2, 2022Assignee: International Business Machines CorporationInventors: Liat Ein Dor, Dalia Krieger, Yonatan Bilu, Noam Slonim
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Patent number: 11341188Abstract: A computerized text analysis method that comprises: searching a resource of information with a search query comprising at least one of: (a) the specific debatable topic, and (b) a personal derivation of the specific debatable topic, to obtain a list of indices whose index subject contains the personal derivation and/or the specific debatable topic; determining, by applying a rule-based classifier, whether the index subject of each of the indices is (i) in favor of the debatable topic or (ii) against the debatable topic; detecting, in each of the indices, hyperlinks to encyclopedic entries whose entry subjects are person names; and determining that: if the index subject of each of the one or more indices is in favor of the specific debatable topic, then the persons are in favor of the specific debatable topic, and vice versa.Type: GrantFiled: June 27, 2019Date of Patent: May 24, 2022Assignee: International Business Machines CorporationInventors: Roy Bar-Haim, Noam Slonim, Orith Toledo-Ronen
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Publication number: 20220147574Abstract: A computerized text analysis method that comprises: searching a resource of information with a search query comprising at least one of: (a) the specific debatable topic, and (b) a personal derivation of the specific debatable topic, to obtain a list of indices whose index subject contains the personal derivation and/or the specific debatable topic; determining, by applying a rule-based classifier, whether the index subject of each of the indices is (i) in favor of the debatable topic or (ii) against the debatable topic; detecting, in each of the indices, hyperlinks to encyclopedic entries whose entry subjects are person names; and determining that: if the index subject of each of the one or more indices is in favor of the specific debatable topic, then the persons are in favor of the specific debatable topic, and vice versa.Type: ApplicationFiled: June 27, 2019Publication date: May 12, 2022Inventors: ROY BAR-HAIM, Noam Slonim, Orith Toledo-Ronen
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Patent number: 11308419Abstract: A method including: generating, from a text corpus, a lexicon of unigrams and bigrams comprising an embedding for each of said unigrams and bigrams; training a machine learning classifier on a training set comprising a subset of said lexicon, wherein each of said unigrams and bigrams in said subset has a sentiment label; applying said machine learning classifier to said lexicon, to (i) predict a sentiment of each of said unigrams and bigrams, and (ii) update said lexicon with the predicted sentiments; and performing statistical analysis on said updated lexicon, to extract one or more sentiment composition lexicons, wherein each of said one or more sentiment composition lexicons is associated with a sentiment composition class.Type: GrantFiled: November 15, 2018Date of Patent: April 19, 2022Assignee: International Business Machines CorporationInventors: Ranit Aharonov, Roy Bar-Haim, Alon Halfon, Charles Arthur Jochim, Amir Menczel, Noam Slonim, Orith Toledo-Ronen
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Publication number: 20210357432Abstract: Embodiments may provide techniques for clustering using predefined anchors that take into account the knowledge about the anchors. For example, a method of clustering processing may be implemented in a computer comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor, the method comprising: receiving a plurality of points of data to be clustered and a plurality of predefined anchor data points and clustering the plurality of points of data and at least a subset of the predefined anchor data points. Further, the method may include creating a similarity function where anchor points pull stronger than regular points, such that they function as attractors.Type: ApplicationFiled: May 12, 2020Publication date: November 18, 2021Inventors: Liat Ein Dor, DALIA KRIEGER, YONATAN BILU, NOAM SLONIM
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Patent number: 11144719Abstract: A system for identifying in a corpus of documents at least one argument relevant to an identified topic, comprising at least one hardware processor adapted to: producing a plurality of topic-related sentences relevant to the identified topic, each extracted from a document of the corpus of documents; producing a plurality of synthetic documents, each created by appending to a sentence of the plurality of topic-related sentences an identified amount of other sentences extracted from the respective document the topic-related sentence was extracted therefrom; identifying at least one argument relevant to the identified topic by inputting each of the plurality of synthetic documents to at least one machine learning model trained to identify an argument in response to a document; and outputting the at least one argument.Type: GrantFiled: November 27, 2019Date of Patent: October 12, 2021Assignee: International Business Machines CorporationInventors: Yonatan Bilu, Liat Ein Dor, Noam Slonim
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Patent number: 11113471Abstract: A method comprising using at least one hardware processor for: receiving a topic under consideration (TUC) and content relevant to the TUC; detecting one or more claims relevant to the TUC in the content, based on detection of boundaries of the claims in the content; and outputting a list of said detected one or more claims.Type: GrantFiled: January 16, 2018Date of Patent: September 7, 2021Assignee: International Business Machines CorporationInventors: Ehud Aharoni, Yonatan Bilu, Dan Gutfreund, Daniel Hershcovich, Tamar Lavee, Ran Levy, Ruty Rinott, Noam Slonim
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Patent number: 11100287Abstract: Method and apparatus for training and using a classifier for words. Embodiments include receiving a first plurality of sentences comprising a first word that is associated with a class and a second plurality of sentences comprising a second word that is not associated with the class. Embodiments include training a classifier using positive training data for the class that is based on the first plurality of sentences and negative training data for the class that is based on the second plurality of sentences. Embodiments include determining a measure of correlation between a third word and the class by using a sentence comprising the third word as an input to the classifier. Embodiments include using the measure of correlation to perform an action selected from the following list: selecting content to provide to a user; determining an automatic chat response; or filtering a set of content.Type: GrantFiled: October 30, 2018Date of Patent: August 24, 2021Assignee: International Business Machines CorporationInventors: Ella Rabinovich, Benjamin Sznajder, Artem Spector, Ilya Shnayderman, Ranit Aharonov, David Konopnicki, Noam Slonim
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Publication number: 20210256214Abstract: Automated detection of reasoning in arguments. A training set is generated by: obtaining multiple arguments, each comprising one or more sentences provided as digital text; automatically estimating a probability that each of the arguments includes reasoning, wherein the estimating comprises applying a contextual language model to each of the arguments; automatically labeling as positive examples those of the arguments which have a relatively high probability to include reasoning; and automatically labeling as negative examples those of the arguments which have a relatively low probability to include reasoning. Based on the generated training set, a machine learning classifier is automatically trained to estimate a probability that a new argument includes reasoning. The trained machine learning classifier is applied to the new argument, to estimate a probability that the new argument includes reasoning.Type: ApplicationFiled: February 13, 2020Publication date: August 19, 2021Inventors: Avishai Gretz, Edo Cohen-Karlik, Noam Slonim, Assaf Toledo
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Publication number: 20210157980Abstract: A system for identifying in a corpus of documents at least one argument relevant to an identified topic, comprising at least one hardware processor adapted to: producing a plurality of topic-related sentences relevant to the identified topic, each extracted from a document of the corpus of documents; producing a plurality of synthetic documents, each created by appending to a sentence of the plurality of topic-related sentences an identified amount of other sentences extracted from the respective document the topic-related sentence was extracted therefrom; identifying at least one argument relevant to the identified topic by inputting each of the plurality of synthetic documents to at least one machine learning model trained to identify an argument in response to a document; and outputting the at least one argument.Type: ApplicationFiled: November 27, 2019Publication date: May 27, 2021Inventors: Yonatan Bilu, Liat Ein Dor, Noam Slonim
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Publication number: 20200410010Abstract: A computerized text analysis method that comprises: searching a resource of information with a search query comprising at least one of: (a) the specific debatable topic, and (b) a personal derivation of the specific debatable topic, to obtain a list of indices whose index subject contains the personal derivation and/or the specific debatable topic; determining, by applying a rule-based classifier, whether the index subject of each of the indices is (i) in favor of the debatable topic or (ii) against the debatable topic; detecting, in each of the indices, hyperlinks to encyclopedic entries whose entry subjects are person names; and determining that: if the index subject of each of the one or more indices is in favor of the specific debatable topic, then the persons are in favor of the specific debatable topic, and vice versa.Type: ApplicationFiled: June 27, 2019Publication date: December 31, 2020Inventors: ROY BAR-HAIM, Noam Slonim, Orith Toledo-Ronen
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Patent number: 10831793Abstract: A method of estimating a thematic similarity of sentences, comprising receiving a corpus of a plurality of documents describing a plurality of topics where each document comprises a plurality of sentences arranged in a plurality of sections, constructing sentence triplets for at least some of the sentences, each sentence triplet comprising a respective sentence, a respective positive sentence selected randomly from the section comprising the respective sentence and a respective negative sentence selected randomly from another section, training a first neural network with the sentence triplets to identify sentence-sentence vectors mapping each sentence with a shorter distance to its respective positive sentence compared to the distance to its respective negative sentence and outputting the first neural network for estimating thematic similarity between a pair of sentences by computing a distance between the sentence-sentence vectors produced for each sentence of the pair by the first neural network.Type: GrantFiled: October 23, 2018Date of Patent: November 10, 2020Assignee: International Business Machines CorporationInventors: Ranit Aharonov, Liat Ein Dor, Alon Halfon, Yosi Mass, Ilya Shnayderman, Noam Slonim, Elad Venezian
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Patent number: 10810375Abstract: A method comprising: operating at least one hardware processor for: receiving, as input, at least one named entity, modifying said named entity based on a plurality of modification rules to generate a set of candidate named entities corresponding to said named entity, and identifying, for at least one candidate named entity in said set of candidate named entities, an article in a knowledge base of articles, wherein a title of said article matches said candidate named entity.Type: GrantFiled: July 8, 2018Date of Patent: October 20, 2020Assignee: International Business Machines CorporationInventors: Yosi Mass, Amir Menczel, Dafna Sheinwald, Ilya Shnayderman, Noam Slonim
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Patent number: 10776587Abstract: A computer-implemented method, computerized apparatus and computer program product for claim generation, the method comprising: selecting at least one subject according to a given topic; selecting at least one verb from a first data source; selecting at least one object from a second data source; generating one or more candidate claim sentences, each of which composed of a subject selected from the at least one subject, a verb selected from the at least one verb and an object selected from the at least on object; and determining validity of the candidate claim sentences using a machine learning process.Type: GrantFiled: July 11, 2016Date of Patent: September 15, 2020Assignee: International Business Machines CorporationInventors: Yonatan Bilu, Ran Levy, Noam Slonim
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Publication number: 20200134020Abstract: Method and apparatus for training and using a classifier for words. Embodiments include receiving a first plurality of sentences comprising a first word that is associated with a class and a second plurality of sentences comprising a second word that is not associated with the class. Embodiments include training a classifier using positive training data for the class that is based on the first plurality of sentences and negative training data for the class that is based on the second plurality of sentences. Embodiments include determining a measure of correlation between a third word and the class by using a sentence comprising the third word as an input to the classifier. Embodiments include using the measure of correlation to perform an action selected from the following list: selecting content to provide to a user; determining an automatic chat response; or filtering a set of content.Type: ApplicationFiled: October 30, 2018Publication date: April 30, 2020Inventors: Ella Rabinovich, Benjamin Sznajder, Artem Spector, Shnayderman Ilya, RANIT AHARONOV, DAVID KONOPNICKI, Noam Slonim
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Publication number: 20200125673Abstract: A method of estimating a thematic similarity of sentences, comprising receiving a corpus of a plurality of documents describing a plurality of topics where each document comprises a plurality of sentences arranged in a plurality of sections, constructing sentence triplets for at least some of the sentences, each sentence triplet comprising a respective sentence, a respective positive sentence selected randomly from the section comprising the respective sentence and a respective negative sentence selected randomly from another section, training a first neural network with the sentence triplets to identify sentence-sentence vectors mapping each sentence with a shorter distance to its respective positive sentence compared to the distance to its respective negative sentence and outputting the first neural network for estimating thematic similarity between a pair of sentences by computing a distance between the sentence-sentence vectors produced for each sentence of the pair by the first neural network.Type: ApplicationFiled: October 23, 2018Publication date: April 23, 2020Inventors: RANIT AHARONOV, Liat Ein Dor, Alon Halfon, Yosi Mass, IIya Shnayderman, Noam Slonim, ELAD VENEZIAN