Patents by Inventor Jan Puzicha
Jan Puzicha 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: 20220188708Abstract: Systems and methods for analyzing documents are provided herein. A plurality of documents and user input are received via a computing device. The user input includes hard coding of a subset of the plurality of documents, based on an identified subject or category. Instructions stored in memory are executed by a processor to generate an initial control set, analyze the initial control set to determine at least one seed set parameter, automatically code a first portion of the plurality of documents based on the initial control set and the seed set parameter associated with the identified subject or category, analyze the first portion of the plurality of documents by applying an adaptive identification cycle, and retrieve a second portion of the plurality of documents based on a result of the application of the adaptive identification cycle test on the first portion of the plurality of documents.Type: ApplicationFiled: March 1, 2022Publication date: June 16, 2022Inventors: Jan Puzicha, Steve Vranas
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Patent number: 11282000Abstract: Systems and methods for analyzing documents are provided herein. A plurality of documents and user input are received via a computing device. The user input includes hard coding of a subset of the plurality of documents, based on an identified subject or category. Instructions stored in memory are executed by a processor to generate an initial control set, analyze the initial control set to determine at least one seed set parameter, automatically code a first portion of the plurality of documents based on the initial control set and the seed set parameter associated with the identified subject or category, analyze the first portion of the plurality of documents by applying an adaptive identification cycle, and retrieve a second portion of the plurality of documents based on a result of the application of the adaptive identification cycle test on the first portion of the plurality of documents.Type: GrantFiled: December 21, 2017Date of Patent: March 22, 2022Assignee: Open Text Holdings, Inc.Inventors: Jan Puzicha, Steve Vranas
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Publication number: 20220036244Abstract: Systems and methods for analyzing documents are provided herein. A plurality of documents and user input are received via a computing device. The user input includes hard coding of a subset of the plurality of documents, based on an identified subject or category. Instructions stored in memory are executed by a processor to generate an initial control set, analyze the initial control set to determine at least one seed set parameter, automatically code a first portion of the plurality of documents based on the initial control set and the seed set parameter associated with the identified subject or category, analyze the first portion of the plurality of documents by applying an adaptive identification cycle, and retrieve a second portion of the plurality of documents based on a result of the application of the adaptive identification cycle test on the first portion of the plurality of documents.Type: ApplicationFiled: October 18, 2021Publication date: February 3, 2022Inventors: Jan Puzicha, Steve Vranas
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Publication number: 20210224693Abstract: Systems and methods for analyzing documents are provided herein. A plurality of documents and user input are received via a computing device. The user input includes hard coding of a subset of the plurality of documents, based on an identified subject or category. Instructions stored in memory are executed by a processor to generate an initial control set, analyze the initial control set to determine at least one seed set parameter, automatically code a first portion of the plurality of documents based on the initial control set and the seed set parameter associated with the identified subject or category, analyze the first portion of the plurality of documents by applying an adaptive identification cycle, and retrieve a second portion of the plurality of documents based on a result of the application of the adaptive identification cycle test on the first portion of the plurality of documents.Type: ApplicationFiled: April 1, 2021Publication date: July 22, 2021Inventors: Jan Puzicha, Steve Vranas
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Publication number: 20210224694Abstract: Systems and methods for analyzing documents are provided herein. A plurality of documents and user input are received via a computing device. The user input includes hard coding of a subset of the plurality of documents, based on an identified subject or category. Instructions stored in memory are executed by a processor to generate an initial control set, analyze the initial control set to determine at least one seed set parameter, automatically code a first portion of the plurality of documents based on the initial control set and the seed set parameter associated with the identified subject or category, analyze the first portion of the plurality of documents by applying an adaptive identification cycle, and retrieve a second portion of the plurality of documents based on a result of the application of the adaptive identification cycle test on the first portion of the plurality of documents.Type: ApplicationFiled: April 5, 2021Publication date: July 22, 2021Inventors: Jan Puzicha, Steve Vranas
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Publication number: 20210216915Abstract: Systems and methods for analyzing documents are provided herein. A plurality of documents and user input are received via a computing device. The user input includes hard coding of a subset of the plurality of documents, based on an identified subject or category. Instructions stored in memory are executed by a processor to generate an initial control set, analyze the initial control set to determine at least one seed set parameter, automatically code a first portion of the plurality of documents based on the initial control set and the seed set parameter associated with the identified subject or category, analyze the first portion of the plurality of documents by applying an adaptive identification cycle, and retrieve a second portion of the plurality of documents based on a result of the application of the adaptive identification cycle test on the first portion of the plurality of documents.Type: ApplicationFiled: March 29, 2021Publication date: July 15, 2021Inventors: Jan Puzicha, Steve Vranas
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Patent number: 11048762Abstract: Provided herein are systems and methods for user-defined automated document feature modeling, extraction and optimization. In the present disclosure, an end user of an automated document review system can customize and create new data models applicable to a set of focus documents. In addition, an end user of the automated document review system can customize and create new extraction rules applicable to text extraction from the set of focus documents. The user-defined edits to the data model and extraction rules can be further tested in a staging environment, and tested against a ground truth set of documents, before being widely applied to other relevant documents.Type: GrantFiled: March 11, 2019Date of Patent: June 29, 2021Assignee: Open Text Holdings, Inc.Inventors: Jan Puzicha, Jan Stadermann, Chaitanya Muppala, Sangeetha Yanamandra, Ketan Deshpande
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Patent number: 11023828Abstract: Systems and methods for analyzing documents are provided herein. A plurality of documents and user input are received via a computing device. The user input includes hard coding of a subset of the plurality of documents, based on an identified subject or category. Instructions stored in memory are executed by a processor to generate an initial control set, analyze the initial control set to determine at least one seed set parameter, automatically code a first portion of the plurality of documents based on the initial control set and the seed set parameter associated with the identified subject or category, analyze the first portion of the plurality of documents by applying an adaptive identification cycle, and retrieve a second portion of the plurality of documents based on a result of the application of the adaptive identification cycle test on the first portion of the plurality of documents.Type: GrantFiled: January 13, 2017Date of Patent: June 1, 2021Assignee: Open Text Holdings, Inc.Inventors: Jan Puzicha, Steve Vranas
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Publication number: 20210133255Abstract: Electronic discovery using predictive filtering is disclosed herein. An example method includes providing a filtering interface that includes a field value input, a predicted values selector, and a predictor type selector; receiving at least a pivot selected from the field value input and a predicted value from the predicted values selector; searching a plurality of documents based on the pivot and the predicted value selected for any of predictive phrases or predictive concepts; calculating a predictive value for each of the predictive phrases or predictive concepts; and generating a graphical user interface that includes the predictive phrases or predictive concepts in conjunction with their respective predictive value.Type: ApplicationFiled: January 15, 2021Publication date: May 6, 2021Inventors: Jan Puzicha, Joe Federline
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Patent number: 10902066Abstract: Electronic discovery using predictive filtering is disclosed herein. An example method includes providing a filtering interface that includes a field value input, a predicted values selector, and a predictor type selector; receiving at least a pivot selected from the field value input and a predicted value from the predicted values selector; searching a plurality of documents based on the pivot and the predicted value selected for any of predictive phrases or predictive concepts; calculating a predictive value for each of the predictive phrases or predictive concepts; and generating a graphical user interface that includes the predictive phrases or predictive concepts in conjunction with their respective predictive value.Type: GrantFiled: July 23, 2018Date of Patent: January 26, 2021Assignee: OPEN TEXT HOLDINGS, INC.Inventors: Jan Puzicha, Joe Federline
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Patent number: 10762142Abstract: Provided herein are systems and methods for user-defined automated document feature modeling, extraction and optimization. In the present disclosure, an end user of an automated document review system can customize and create new extractor taggers within data models applicable to a set of focus documents. The user-defined edits to the extractor taggers can be further tested in a staging environment, and tested against a ground truth set of documents, before being widely applied to other relevant documents.Type: GrantFiled: April 29, 2019Date of Patent: September 1, 2020Assignee: Open Text Holdings, Inc.Inventors: Jan Puzicha, Jan Stadermann, Chaitanya Muppala, Sangeetha Yanamandra, Ketan Deshpande
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Publication number: 20200026768Abstract: Electronic discovery using predictive filtering is disclosed herein. An example method includes providing a filtering interface that includes a field value input, a predicted values selector, and a predictor type selector; receiving at least a pivot selected from the field value input and a predicted value from the predicted values selector; searching a plurality of documents based on the pivot and the predicted value selected for any of predictive phrases or predictive concepts; calculating a predictive value for each of the predictive phrases or predictive concepts; and generating a graphical user interface that includes the predictive phrases or predictive concepts in conjunction with their respective predictive value.Type: ApplicationFiled: July 23, 2018Publication date: January 23, 2020Inventors: Jan Puzicha, Joe Federline
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Publication number: 20190325031Abstract: Machine learning based predictive document searching systems and methods are disclosed herein. An example method includes displaying on a graphical user interface a list of predictively coded documents; receiving an indication that a portion of the list of predictively coded documents are relevant to a user, the indication including a pinning of the portion of the list of predictively coded documents through user actuation received through the graphical user interface, displaying the pinned portion of the list of predictively coded documents in a pinned document list, applying text categorization to the pinned portion of the list of predictively coded documents, obtaining a recommended set of documents from a corpus of documents based on the text categorization and displaying recommended set of documents to the user on the graphical user interface.Type: ApplicationFiled: April 19, 2018Publication date: October 24, 2019Inventor: Jan Puzicha
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Publication number: 20190286667Abstract: Provided herein are systems and methods for user-defined automated document feature modeling, extraction and optimization. In the present disclosure, an end user of an automated document review system can customize and create new data models applicable to a set of focus documents. In addition, an end user of the automated document review system can customize and create new extraction rules applicable to text extraction from the set of focus documents. The user-defined edits to the data model and extraction rules can be further tested in a staging environment, and tested against a ground truth set of documents, before being widely applied to other relevant documents.Type: ApplicationFiled: March 11, 2019Publication date: September 19, 2019Inventors: Jan Puzicha, Jan Stadermann, Chaitanya Muppala, Sangeetha Yanamandra, Ketan Deshpande
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Publication number: 20190286668Abstract: Provided herein are systems and methods for user-defined automated document feature modeling, extraction and optimization. In the present disclosure, an end user of an automated document review system can customize and create new extractor taggers within data models applicable to a set of focus documents. The user-defined edits to the extractor taggers can be further tested in a staging environment, and tested against a ground truth set of documents, before being widely applied to other relevant documents.Type: ApplicationFiled: April 29, 2019Publication date: September 19, 2019Inventors: Jan Puzicha, Jan Stadermann, Chaitanya Muppala, Sangeetha Yanamandra, Ketan Deshpande
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Publication number: 20190213197Abstract: Systems and methods that quantify document relevance for a document relative to a training corpus and select a best match or best matches are provided herein. Methods may include generating an example-based explanation for relevancy of a document to a training corpus by executing a support vector machine classifier, the support vector machine classifier performing a centroid classification of a relevant document in a term frequency-inverse document frequency features space relative to training examples in a training corpus, and generating an example-based explanation by selecting a best match for the relevant document from the training examples based upon the centroid classification.Type: ApplicationFiled: March 15, 2019Publication date: July 11, 2019Inventors: Christian Feuersänger, Dietrich Wettschereck, Jan Puzicha
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Publication number: 20190205400Abstract: In context document review and automated coding are described herein. An example method includes determining at least one binding between documents, the at least one binding being indicative of a contextual relationship between the documents, selecting a review order for the documents based on the at least one binding, the review order comprising a hierarchical arrangement of the documents, displaying the documents in a graphical user interface based on the review order; and automatically coding the documents based on the at least one binding and control data received through the graphical user interface.Type: ApplicationFiled: December 28, 2017Publication date: July 4, 2019Inventor: Jan Puzicha
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Patent number: 10324936Abstract: Systems and methods that quantify document relevance for a document relative to a training corpus and select a best match or best matches are provided herein. Methods may include generating an example-based explanation for relevancy of a document to a training corpus by executing a support vector machine classifier, the support vector machine classifier performing a centroid classification of a relevant document in a term frequency-inverse document frequency features space relative to training examples in a training corpus, and generating an example-based explanation by selecting a best match for the relevant document from the training examples based upon the centroid classification.Type: GrantFiled: July 26, 2013Date of Patent: June 18, 2019Assignee: Open Text Holdings, Inc.Inventors: Christian Feuersänger, Dietrich Wettschereck, Jan Puzicha
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Publication number: 20180121831Abstract: Systems and methods for analyzing documents are provided herein. A plurality of documents and user input are received via a computing device. The user input includes hard coding of a subset of the plurality of documents, based on an identified subject or category. Instructions stored in memory are executed by a processor to generate an initial control set, analyze the initial control set to determine at least one seed set parameter, automatically code a first portion of the plurality of documents based on the initial control set and the seed set parameter associated with the identified subject or category, analyze the first portion of the plurality of documents by applying an adaptive identification cycle, and retrieve a second portion of the plurality of documents based on a result of the application of the adaptive identification cycle test on the first portion of the plurality of documents.Type: ApplicationFiled: December 21, 2017Publication date: May 3, 2018Inventors: Jan Puzicha, Steve Vranas
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Publication number: 20170322931Abstract: Methods and systems of integrated batching and random sampling of documents for enhanced functionality and quality control, such as validation, within a document review process are provided herein. According to various embodiments, a batching request may be received and may include a population size that corresponds to a total amount of documents available for sampling. The batching request may also include an acceptable margin of error. A random sample size may be calculated based on the batching request, and then a subset of documents corresponding to the random sample size may be selected from the total amount of documents available for sampling. The subset of documents may be grouped into one or more batches, and the one or more batches may be assigned to one or more review nodes.Type: ApplicationFiled: July 21, 2017Publication date: November 9, 2017Inventor: Jan Puzicha