Abstract: A method for automatically converting note-to-self to action reminders in an electronic device is provided. The method includes receiving an input comprising at least one word from a user of the electronic device, analyzing an anaphora representation or a deictic representation for each of the at least one word, and generating a reminder based on a context from the anaphora representation or the deictic representation.

Abstract: A method for automatically converting note-to-self to action reminders in an electronic device is provided. The method includes receiving an input comprising at least one word from a user of the electronic device, analyzing an anaphora representation or a deictic representation for each of the at least one word, and generating a reminder based on a context from the anaphora representation or the deictic representation.

Abstract: The technique relates to a system and method for data-driven anomaly detection. This technique involves identifying region of interest from the data based on dimensionality reduction technique and change point detection algorithm. A reference data can be obtained separately or can be obtained from the test data also, wherein the reference data represent the normal operating condition of a system. The reference data are classified into different groups representing different modes of operation of the system. A control limit is determined for the different groups. The data within the region of interest are mapped with the different groups of the reference data and it is determined if the mapped data fall outside of the control limit of the mapped group. Finally, at least one abnormal event is detected by applying a heuristic algorithm on the data within the region of interest which are outside the control limit.

Abstract: A method for automatically converting note-to-self to action reminders in an electronic device is provided. The method includes receiving an input comprising at least one word from a user of the electronic device, analyzing an anaphora representation or a deictic representation for each of the at least one word, and generating a reminder based on a context from the anaphora representation or the deictic representation.

Abstract: The technique relates to a system and method for mining frequent and in-frequent items from a large transaction database to provide the dynamic recommendation of items. The method involves determining user interest for an item by monitoring short item behavior of at least one user then selecting a local category, a neighborhood category and a disjoint category with respect to the item clicked by the at least one user based on long term preferences data of a plurality of users of the ecommerce environment thereafter selecting one or more frequent and infrequent items from each of the selected local, neighborhood and disjoint category items and finally generating one or more dynamic recommendations based on the one or more items selected from the local category, the neighborhood category and the disjoint category and the one or more selected frequent and infrequent items.

Abstract: A method for automatically converting note-to-self to action reminders in an electronic device is provided. The method includes receiving an input comprising at least one word from a user of the electronic device, analyzing an anaphora representation or a deictic representation for each of the at least one word, and generating a reminder based on a context from the anaphora representation or the deictic representation.

Abstract: A method and system for identifying episodic events in a user's life using an electronic device are provided. The method includes receiving, by the electronic device, unstructured data from at least one data source associated with a user, and identifying at least one episodic event from the unstructured data based on at least one parameter, wherein the at least one parameter is at least one of a casual reasoning, a spatial reasoning, or a temporal reasoning.

Abstract: The technique relates to a system and method for mining frequent and in-frequent items from a large transaction database to provide the dynamic recommendation of items. The method involves determining user interest for an item by monitoring short item behavior of at least one user then selecting a local category, a neighborhood category and a disjoint category with respect to the item clicked by the at least one user based on long term preferences data of a plurality of users of the ecommerce environment thereafter selecting one or more frequent and infrequent items from each of the selected local, neighborhood and disjoint category items and finally generating one or more dynamic recommendations based on the one or more items selected from the local category, the neighborhood category and the disjoint category and the one or more selected frequent and infrequent items.

Abstract: A method for generating feature graphs employed for creation of a head note in a legal document is provided. The method enables identifying one or more predetermined features in a plurality of legal documents. The one or more predetermined features are based on grammatical constituents of text in the legal document. The plurality of legal documents is manually identified as headnote and non headnote. The method further enables obtaining data related to the availability of the one or more identified predetermined features in the sentences manually identified as headnote and non headnote in the plurality of legal documents. Furthermore, the method enables computing likelihood of a sentence being a headnote based on the obtained data. The method further enables generating feature graphs corresponding to each predetermined feature based on the computed likelihood and obtained data and storing the generated feature graphs in a repository.

Abstract: The technique relates to a system and method for data-driven anomaly detection. This technique involves identifying region of interest from the data based on dimensionality reduction technique and change point detection algorithm. A reference data can be obtained separately or can be obtained from the test data also, wherein the reference data represent the normal operating condition of a system. The reference data are classified into different groups representing different modes of operation of the system. A control limit is determined for the different groups. The data within the region of interest are mapped with the different groups of the reference data and it is determined if the mapped data fall outside of the control limit of the mapped group. Finally, at least one abnormal event is detected by applying a heuristic algorithm on the data within the region of interest which are outside the control limit.

Abstract: A system, method and computer program product for forecasting one or more clinical pathways and resource requirements of at least one patient are provided. The system comprises an input module for receiving inputs pertaining to patient diagnostic data, the patient diagnostic data comprising information identified during diagnosis of the patient. The system also comprises a repository for storing data comprising at least one of patient data and pre-existing clinical pathways. The patient data comprises at least one of the patient diagnostic data received from the input module; patient historical data comprising historical treatment data of the patient and patient demographic data comprising demographic details of the patient. The system also comprises a clinical pathway forecasting module for forecasting clinical pathways by application of predetermined analytical models on the patient data and pre-existing clinical pathways.

Abstract: A method for designing identity plates which are placed on corresponding shopping carts is provided. A unique identity data is represented on each identity plate using an identification code. The unique identity data is encoded employing symbols having distinct physical characteristics. The association between the symbols and the identification code is predetermined. The method enables identifying shopping carts by capturing images of the shopping carts using video sensors and decoding identity data on each identity plate placed on each shopping cart. The identity data is decoded by recognizing symbols based on physical characteristics and translating recognized symbols to corresponding identity data referring to the predetermined association between the symbols and identification code. Identity data of shopping carts, identity data of video sensors and timestamp information is used for identifying location of video sensors using which path taken by shopping carts in the retail store is tracked.

Abstract: A method for generating feature graphs employed for creation of a head note in a legal document is provided. The method enables identifying one or more predetermined features in a plurality of legal documents. The one or more predetermined features are based on grammatical constituents of text in the legal document. The plurality of legal documents is manually identified as headnote and non headnote. The method further enables obtaining data related to the availability of the one or more identified predetermined features in the sentences manually identified as headnote and non headnote in the plurality of legal documents. Furthermore, the method enables computing likelihood of a sentence being a headnote based on the obtained data. The method further enables generating feature graphs corresponding to each predetermined feature based on the computed likelihood and obtained data and storing the generated feature graphs in a repository.

Abstract: The disclosed embodiment relates to methods, systems, and computer readable code for establishing transshipment of a product between stocking locations. The exemplary method comprises the steps of transmitting a transshipment request to at least one supplier requesting transshipment of a product, the transshipment request including information regarding the product and specifying a reward for transshipment of the product, receiving a handshake request from one of the suppliers in response to the transshipment request, the handshake request indicating the willingness of the one of the suppliers to provide the product as specified in the transshipment request and including information regarding the transshipment; and accepting the handshake request, thereby initiating transshipment of the product from the one of the suppliers in accordance with the accepted handshake request.

Abstract: A method for designing identity plates which are placed on corresponding shopping carts is provided. A unique identity data is represented on each identity plate using an identification code. The unique identity data is encoded employing symbols having distinct physical characteristics. The association between the symbols and the identification code is predetermined. The method enables identifying shopping carts by capturing images of the shopping carts using video sensors and decoding identity data on each identity plate placed on each shopping cart. The identity data is decoded by recognizing symbols based on physical characteristics and translating recognized symbols to corresponding identity data referring to the predetermined association between the symbols and identification code. Identity data of shopping carts, identity data of video sensors and timestamp information is used for identifying location of video sensors using which path taken by shopping carts in the retail store is tracked.

Abstract: A system, method and computer program product for forecasting one or more clinical pathways and resource requirements of at least one patient are provided. The system comprises an input module for receiving inputs pertaining to patient diagnostic data, the patient diagnostic data comprising information identified during diagnosis of the patient. The system also comprises a repository for storing data comprising at least one of patient data and pre-existing clinical pathways. The patient data comprises at least one of the patient diagnostic data received from the input module; patient historical data comprising historical treatment data of the patient and patient demographic data comprising demographic details of the patient. The system also comprises a clinical pathway forecasting module for forecasting clinical pathways by application of predetermined analytical models on the patient data and pre-existing clinical pathways.