Intelligent NEWS Search System.

Abstract

Content based information retrieval is a complex process which requires combination of several techniques and processes to produce accurate results. Natural Language Processing has enabled the field of AI which provide computer to understand natural way of how humans communicate by combination of machine learning, deep learning, and statistical models. Rate of flow of information on the other hand is also increasing daily. Searching an entity, user often has no idea about the exact name of the person, hearing about respective entity or a nickname is mainly used in public by people which is heard. Searching on engines do not provide the exactly relevant information regarding that person’s nickname or any other title he/she is pronounced with in public. There are no such systems which can mine the exact information regarding a query and provide query relevant information. Khabar – Intelligent News Search System is NLP based news search engine which can mine information and provide query-relevant information extracted from E-news paper against a user-query. System uses powerful NLP algorithms and techniques to produce fast and accurate results. Fast Text model and BM25 techniques have made this search engine efficient in terms of information retrieval. Query auto completion is also embedded in the system to assist the user. The target audience is news reporting agencies. With an integration of several other modules information extraction can be more precise and accurate