International Business Machines Corporation

Amazon Technologies, Inc.

Ran Levy

Noam Slonim

Ehud Aharoni

Dan Gutfreund

Ruty Rinott

Tamar Lavee

Yonatan Bilu

Daniel Hershcovich

David Carmel

Iftah Gamzu

Eyal Shnarch

Leon Portman

Lena Dankin

Knaan Ratosh

Ido Arad

Hadar Neumann

Yehuda Finkelstein

Haim Litvak

Ori Rozen

Systems and methods are described herein for generating an adaptive response to a user request. Input indicative of a user request may be received and utilized to identify an item in an electronic catalog. Title segments may be identified from the item's title. Significant segments of the user request may be determined. In response to the user request, a shortened title may be generated from the identified title segments and provided as output at the user device (e.g., via audible output provided at a speaker of the user device, via textual output, or the like). At least one of the title segments provided in the shortened title may correlate to the significant segment identified from the user request. In some embodiments, the length and content of the shortened title may vary based at least in part on the contextual intent of the user's request.

Techniques for providing adaptive responses

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.

Automatic detection of claims with respect to a topic

Systems and methods are described herein for generating adaptive feedback in response to a user request. Input indicative of a user request may be received and utilized to identify an item in an electronic catalog. A title for the item may be retrieved and provided, as input, to a machine-learning model. The machine-learning model may be trained to identify one or more segments of an input title. A shortened title may be generated from these identified segments and provided as output at the user device (e.g., via audible output provided at a speaker of the user device). In some embodiments, the length and content of the shortened title may vary based at least in part on the contextual intent of the user's request.

Techniques to provide adaptive feedback

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.

Claim generation

A method comprising using at least one hardware processor for receiving a topic under consideration (TUC); providing the TUC as input to a claim function, wherein the claim function is configured to mine at least one content resource, and applying the claim function to the at least one content resource, to extract claims with respect to the TUC; and providing the TUC as input to a classification function, and applying the classification function to one or more claims of the extracted claims, to output corresponding one or more classification tags, wherein each classification tag is associated with its corresponding claim.

Automatic construction of arguments

There is provided a computer-implemented method for outputting one or more cross-layer patterns to identify a target semantic phenomenon in text, the method comprising: extracting, for each word of at least some words of each training text fragment of training text fragments designated as representing a target semantic phenomenon, feature-values defined by respective layers; statistically analyzing the feature-values identified for the training text fragments to identify one or more cross-layer patterns comprising layers representing a common pattern for the training text fragments, the common cross-layer pattern defining one or more feature-values of a respective layer of one or more words and at least another feature-value of another respective layer of another word; and outputting the identified cross-layer pattern(s) for identifying a text fragment representing the target semantic phenomenon.

Systems and methods for language feature generation over multi-layered word representation

A method comprising using at least one hardware processor for: receiving a context; identifying evidence with respect to the context in at least one content resource, wherein the identifying comprises: identifying context-free features that generally characterize evidence in the at least one content resource, and identifying context features indicative of the relevance of text segments in the at least one content resource to the context; and outputting a list of said identified evidence.

Context-dependent evidence detection

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Givatayim, Israel

Ran Levy