International Business Machines Corporation

Laura J Bennett

Lakshminarayanan Krishnamurthy

Sridhar Sudarsan

Niyati Parameswaran

Lior Aronovich

Partho Ghosh

Christopher Joseph Paul

Scott Michael Consolatti

Stephen Ronald Haertel

Jenna Lau Caruso

Samaya Madhavan

Anamita Guha

Geetha Kola

A computer-implemented system and method operate an automatic and adaptive animal behavioral system. The system receives user configuration and feedback, and generates a training set based on online animal behavior patterns and received user feedback. The system trains one or multiple models based on the training set, if the training set is sufficiently large. It then validates the models, and provides system generated classifications and action types and levels for animal's behavior patterns, if the models' accuracy rate is above a threshold.

Operating an automated and adaptive animal behavioral training system using machine learning

The exemplary embodiments disclose a method, a computer program product, and a computer system for managing sanitation. The exemplary embodiments may include collecting data of one or more assets, extracting one or more features from the collected data, and evaluating a state of sanitation of the one or more assets based on applying one or more models to the extracted features.

Sanitation management based on digital twin

A system, method, and computer-readable medium are disclosed for identifying paraphrases in a natural language processing (NLP) system comprising: receiving a first phrase and a second phrase by a system; analyzing the first phrase and the second phrase to provide a semantic and structural hierarchical comparison assessment, the semantic and structural hierarchical comparison assessment having an associated semantic and structural hierarchical comparison assessment value; and determining whether the semantic and structural hierarchical comparison assessment value exceeds a predetermined paraphrase equivalency criteria; and, responsive to determining the semantic and structural hierarchical comparison assessment value exceeds the predetermined paraphrase equivalency criteria, classifying the second phrase as being a rewording of the first phrase.

Automatic, unsupervised paraphrase detection

A method is disclosed for identifying paraphrases in a natural language processing (NLP) system comprising: receiving a first phrase and a second phrase by a system; analyzing the first phrase and the second phrase to provide a semantic and structural hierarchical comparison assessment, the semantic and structural hierarchical comparison assessment having an associated semantic and structural hierarchical comparison assessment value; and determining whether the semantic and structural hierarchical comparison assessment value exceeds a predetermined paraphrase equivalency criteria; and, responsive to determining the semantic and structural hierarchical comparison assessment value exceeds the predetermined paraphrase equivalency criteria, classifying the second phrase as being a rewording of the first phrase.

A system includes a question answering system executed by a computer, a processor, and a memory coupled to the processor. The memory is encoded with instructions that when executed cause the processor to provide training for training the question answering system. The training system is configured to receive a first phrase and a second phrase, the first and second phrases being paraphrases of each other, convert the first phrase into a first logical form and the second phrase into a second logical form, generate a phrasal edit that includes a difference between the first logical form and the second logical form, convert the phrasal edit into a disjunctive logical form in two directions, and generate a first plurality of paraphrases of the first and second phrases based on the disjunctive logical form.

System and method for automatic, unsupervised paraphrase generation using a novel framework that learns syntactic construct while retaining semantic meaning

A system includes a question answering system executed by a computer, a processor, and a memory coupled to the processor. The memory is encoded with instructions that when executed cause the processor to provide training for training the question answering system. The training system is configured to receive a plurality of bidirectional disjunctive logical forms which include two directional disjunctions of differences between a first logical form of a first sentence and second logical form of a second sentence, realize the plurality of bidirectional disjunctive logical forms to generate a first plurality of paraphrases of the first and second sentence, score each of the first plurality of paraphrases based on textual similarity between the first plurality of paraphrases and the first and second sentences, and prune the first plurality of paraphrases to generate a second plurality of paraphrases based on the scores of each of the first plurality of paraphrases.

Application software is visually programmed with a relational diagram that is structured in a left-to-right format. Parts/beans of a software application are placed onto the relational diagram to illustrate an inherent visual flow of the application's logic. The relational diagram is further structured by providing a three column workspace for display of the parts/beans of the software application. The three column workspace can be further structured with a center column for placement of a main part/bean. A left most column is also provided for placement of others of the parts/beans which provide input to the main part/bean in the center column. In addition, a right most column is provided for placement of other parts/beans which receive output from the main part/bean in the center column. The application logic can be modified when a user adds at least one of the parts/beans directly to any one of the three columns in the workspace.

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San Francisco, CA, United States of America

Laura J Bennett