Abstract: A method for detecting point anomaly in a text data is disclosed. The method may include tokenizing text input comprising a plurality of text entities into a plurality of tokens, annotating, by the point anomaly detection device, the plurality of tokens, based on one or more annotation parameters. One or more annotation parameters comprise a part-of-speech, a sentiment polarity, a negation statement, and domain rules. The method further includes identifying from one or more annotated tokens, at least one of: one or more anomaly subject tokens, one or more anomaly type tokens, and one or more action type tokens from plurality of tokens. The method further includes generating inferences based on the identified one or more anomaly type tokens, the one or more action type tokens from the plurality of tokens, and the one or more annotation parameters.

Abstract: A method for detecting point anomaly in a text data is disclosed. The method may include tokenizing text input comprising a plurality of text entities into a plurality of tokens, annotating, by the point anomaly detection device, the plurality of tokens, based on one or more annotation parameters. One or more annotation parameters comprise a part-of-speech, a sentiment polarity, a negation statement, and domain rules. The method further includes identifying from one or more annotated tokens, at least one of: one or more anomaly subject tokens, one or more anomaly type tokens, and one or more action type tokens from plurality of tokens. The method further includes generating inferences based on the identified one or more anomaly type tokens, the one or more action type tokens from the plurality of tokens, and the one or more annotation parameters.

Abstract: This disclosure relates to a method and system for extracting information from contents of an input file. The method may include identifying text data from the input file, receiving a text input from a user for identifying relevant text entities from the plurality of text entities, and automatically generating a search pattern corresponding to the text input. The method may further include determining a pattern associated with each of the plurality of text entities, and mapping the search pattern corresponding to the text input with patterns associated with the plurality of text entities. The method may further include identifying one or more matching patterns from the patterns associated with the plurality of text entities based on the mapping, and extracting, from the plurality of text entities, relevant text entities corresponding to the one or more matching patterns.