Innoplexus Ag

6sense Insights, Inc.

Rohit Kewalramani

Vatsal Agarwal

Gaurav Tripathi

Justin Chien

Dileep Dharma

Prashant Neminath Patil

Jijeesh Kr

Machine-learning-aided automatic taxonomy for web data. In an embodiment, a training dataset of annotated features is used to train a model to predict a class in a taxonomy of web-based activities. The features may be derived from a uniform resource locator (URL) of an online resource and associated metadata. During operation, the features may be extracted from the URL and metadata of each activity record in web data. The trained model may be applied to the extracted features for each activity record to predict a class within the taxonomy. The predicted taxonomic class may be stored in association with the URL that was extracted from the activity record to produce a taxonomized URL.

Machine-learning-aided automatic taxonomy for web data

Machine learning aided automatic taxonomy for web data

A system and a method for parsing a user query. The system includes a database arrangement operable to store an ontology; and a processing module communicably coupled to the database arrangement. The processing module operable to receive the user query; refine the user query to obtain a search query using an algorithm; generate a plurality of strings for the obtained search query; sort the plurality of strings in a decreasing order of length of the plurality of strings; assign a part-of-speech tag to each of the query segments of the plurality of strings based on the ontology; identify at least one of the query segments as at least one output class or at least one input class based on the assigned part-of-speech tags; and establish semantic associations between the query segments based on the ontology to obtain the parsed user query.

System and method for parsing user query

A method and system for generating a parsed document from a digital document. The method includes segmenting the digital document into at least one section; classifying the at least one section of the digital document into at least one of a class: text class, table class, figure class, noise class; identifying a reading order of the digital document; and processing each of the at least one section of the digital document. Furthermore, processing each of the at least one section of the digital document comprises extracting content from each of the at least one section based on the class; and structuring the extracted content based on the reading order to generate the parsed document.

Method and system for generating parsed document from digital document

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Pune, India

Rohit Kewalramani