Abstract: A method and a system are described for context based clustering of one or more objects. The method comprises receiving, by the object clustering system, receiving, by an object clustering system, an object clustering request for one or more objects associated with a plurality of contextual parameters, where the plurality of contextual parameters comprises one or more physical attributes and one or more non-physical attributes. It further includes tagging the one or more non-physical attributes respectively to the one or more physical attributes. It further includes identifying a common context from the one or more physical attributes associated with the one or more objects based on the tagging. It further includes mapping the one or more physical attributes to the one or more objects based on the common context. It then includes clustering the one or more objects based on the mapping.

Abstract: A method for detecting outliers is provided, the method comprising: receiving a digitized text corpus comprising a plurality of data points; identifying k clusters of the plurality of data points; sampling a data point among the plurality of data points as a first cluster center of the k clusters; determining sampling probability of each of remaining data points of the plurality of data points; sampling the next cluster center based on the sampling probability and iterate the process of determining sampling probability and the process of sampling the next cluster center until k cluster centers are sampled; generating weightage for each of the k cluster centers; determining sensitivity scores of the data points belonging to each of the k cluster centers; and labeling a data point having a sensitivity score greater than a threshold value as an outlier and removing the outlier from the digitized text corpus.

Abstract: This disclosure relates to method, device, Wand system for clustering document objects based on information content. The method may include identifying a plurality of object chunks from at least one document based on semantic context of each of the plurality of object chunks, determining at least one document portion from the at least one document as a base document based on a plurality of parameters applied to the plurality of object chunks, determining a plurality of hierarchies within the base document, and categorizing the plurality of object chunks based on the plurality of hierarchies and information in each of the plurality of object chunks. It should be noted that each of the plurality of object chunks may include at least one object selected from the at least one document.

Abstract: A method and a system are described for context based clustering of one or more objects. The method comprises receiving, by the object clustering system, receiving, by an object clustering system, an object clustering request for one or more objects associated with a plurality of contextual parameters, where the plurality of contextual parameters comprises one or more physical attributes and one or more non-physical attributes. It further includes tagging the one or more non-physical attributes respectively to the one or more physical attributes. It further includes identifying a common context from the one or more physical attributes associated with the one or more objects based on the tagging. It further includes mapping the one or more physical attributes to the one or more objects based on the common context. It then includes clustering the one or more objects based on the mapping.

Abstract: This disclosure relates to method, device, Wand system for clustering document objects based on information content. The method may include identifying a plurality of object chunks from at least one document based on semantic context of each of the plurality of object chunks, determining at least one document portion from the at least one document as a base document based on a plurality of parameters applied to the plurality of object chunks, determining a plurality of hierarchies within the base document, and categorizing the plurality of object chunks based on the plurality of hierarchies and information in each of the plurality of object chunks. It should be noted that each of the plurality of object chunks may include at least one object selected from the at least one document.

Abstract: A method for detecting outliers is provided, the method comprising: receiving a digitized text corpus comprising a plurality of data points; identifying k clusters of the plurality of data points; sampling a data point among the plurality of data points as a first cluster center of the k clusters; determining sampling probability of each of remaining data points of the plurality of data points; sampling the next cluster center based on the sampling probability and iterate the process of determining sampling probability and the process of sampling the next cluster center until k cluster centers are sampled; generating weightage for each of the k cluster centers; determining sensitivity scores of the data points belonging to each of the k cluster centers; and labeling a data point having a sensitivity score greater than a threshold value as an outlier and removing the outlier from the digitized text corpus.