Abstract: Described are methods and systems for parsing unstructured or semi-structured text to extract named entities, data types defined to include semantic fields. Fields are constrained to sets of potential field values. These sets can overlap, leading to ambiguous parses. For example, the text string “3-4-2023” parsed as a date can yield Mar. 4, 2023 or Apr. 3, 2023. Potential field values in alternative parses are scored and the scores used to select and disambiguate the resultant value parses.

Abstract: Described are methods and systems for graphically organizing words and their meanings. The words, in an input language such as English, are added as nodes to a graph. Synonyms of each input word taken from a second language, such as Sanskrit, are likewise added as nodes to the graph and connected to the corresponding input-word nodes via synonym edges. Root elements of the synonyms, semantic meanings, are also added to the graph as meaning nodes. The resulting graph depicts linguistic and semantic interrelations between input words, their second-language synonyms, and the meanings derived therefrom.

Abstract: A semantic analyzer uses the morphological semantics of Sanskrit to extract numerical representations, or embeddings, from English words. The analyzer finds Sanskrit synonyms for the English input word and deconstructs them into their constituent Dhatus, or morphological units, using Sanskrit morphological rules known as Pratyayas. The meanings of the Dhatus are then used to disambiguate the meaning of the input word. These Dhatu constituents describe the semantic attributes of the word's denotation, forming an embedding of the input word. This low-dimensional vector representation of the word's meaning can be used for various tasks requiring natural language understanding. The Dhatu vectors define a logic of natural-language words, capturing specific semantic attributes to support semantic models with improved interpretability and reasoning power.

Abstract: The present invention provides system and method for adaptive application and privacy preserving internet of things. The system comprises of at least one configured IoT device(s) (A) for receiving, processing, filtering, storing and transferring limited information to at least one receiving IoT device(s) (R1, R2, . . . , Rn), at least one inputting IoT device(s) (ID1, ID2, . . . IDn) for transferring information to said IoT device(s) (A), at least one memory unit (M) for storing processed information in said configured IoT device (A), at least one communication interface (C) for communication between IoT device(s), at least one receiving IoT device(s) (R1, R2, . . . Rn) to receive processed information from said configured IoT device (A) as per the information flow policies (P) thereby limiting the type and amount of private information that can be supplied or leaked to the public from one IoT device irrespective of the application running on the IoT device.