Abstract: The present invention discloses a method and a system for clustering of short and long text documents. The documents are input through an input module and a pre-processing module overtakes the documents from the input module. The pre-processing module refines the documents and removes unwanted text from the documents. Then a decision driven hybrid text clustering algorithm is applied via different modules to achieve clustering of the documents. Firstly, a context module computes a moment value of a feature signifying at least one feature importance value of the feature for the documents. The moment value is used by a decision module to calculate a decision score. Based on the decision score the documents are split into two sets. A clustering module then forms clusters of the two sets of documents based on n-tuple word distribution. Finally, a convergence module congregates the clusters in a final set of documents.

Abstract: The present invention discloses a system and method with associated feature capabilities for analyzing and resolving tickets raised in an IT environment. The system monitors health of multiple assets included in the environment and in case an alert is triggered, the system further analyses the alert and provides a recommendation on conversion of the alert to an incident ticket. The incident ticket can also be reported manually by human. Such tickets are then categorized based on certain influencing factors. To this end, a best possible resolution for each incident ticket is then recommended. Subsequently, automatic resolution scripts are identified intelligently and automatically to resolve the problem.

Abstract: The present invention discloses a method and a system for clustering of short and long text documents. The documents are input through an input module and a pre-processing module overtakes the documents from the input module. The pre-processing module refines the documents and removes unwanted text from the documents. Then a decision driven hybrid text clustering algorithm is applied via different modules to achieve clustering of the documents. Firstly, a context module computes a moment value of a feature signifying at least one feature importance value of the feature for the documents. The moment value is used by a decision module to calculate a decision score. Basis the decision score the documents are split into two sets. A clustering module then forms clusters of the two sets of documents basis n-tuple word distribution. Finally, a convergence module congregates the clusters in a final set of documents.

Abstract: The present invention discloses a system and method with associated feature capabilities for analyzing and resolving tickets raised in an IT environment. The system monitors health of multiple assets included in the environment and in case an alert is triggered, the system further analyses the alert and provides a recommendation on conversion of the alert to an incident ticket. The incident ticket can also be reported manually by human. Such tickets are then categorized based on certain influencing factors. To this end, a best possible resolution for each incident ticket is then recommended. Subsequently, automatic resolution scripts are identified intelligently and automatically to resolve the problem.

Abstract: Systems and methods for cognitive information mining are provided. A cognitive information extraction system provides intelligent information extraction from documents in different formats, types and forms. Since a huge portion of the data and information is still stored in unstructured documents in physical format, the system provides for a framework to extract information from such documents. Further, even in the digital form, the documents are available in multiple different formats, which can act as a great hindrance to useful extract information. The invention focuses upon mitigating this scenario by combining multiple AI models and modules to create a framework for document processing and human-machine interaction for training and QC verification, wherein the framework provides user the flexibility to work upon multiple types of documents, and also ensures that accuracy is maintained while the information is being extracted.

Abstract: Described herein are methods and systems for performing functions associated with a non-functional key of a keyboard present on electronic devices such as cell-phones, telephones, ATMs, etc. The electronic device is operated in a non-functional key (NFK) coding mode using NFK codes (108) that are provided to a memory component (202) of the electronic device (102). In the NFK coding mode, a user is allowed to enter functional keys in a coded sequence. Based on the NFK codes (108), the coded sequence is used to identify a function associated with a non-functional key of the keyboard and the identified function is indicated to a processor (204) of the electronic device (102) for execution.

Abstract: Described herein are methods and systems for performing functions associated with a non-functional key of a keyboard present on electronic devices such as cell-phones, telephones, ATMs, etc. The electronic device is operated in a non-functional key (NFK) coding mode using NFK codes (108) that are provided to a memory component (202) of the electronic device (102). In the NFK coding mode, a user is allowed to enter functional keys in a coded sequence. Based on the NFK codes (108), the coded sequence is used to identify a function associated with a non-functional key of the keyboard and the identified function is indicated to a processor (204) of the electronic device (102) for execution.