Crime information extraction from news articles

Abstract

In the modern era all news reportings are available in digital form. Most newsagencies put it on their website and are freely available. This motivates us totry extracting some information from online news reporting. While understandingnatural language text for information extraction is a complex task,we hopethat extracting information like crime type, crime location, and some profile informationof accused and victim should be feasible. In this work we pulled about1000 crime news articles from NDTV and Indian Express websites. Hand taggingwas done for crime location and crime types of all articles. Through this workwe show that a combination of LSTM and CNN based solution can be effectivelyused for extracting crime location. Using this technique we get 95.58 % precisionand 94.54 % recall. Further, determination of crime type, we found relatively easier.Through simple key word based classification approach we get 95% precision.We also tried out topic modeling for crime type extraction we do not gain any improvement,and we get 79 % precision. Keywords: crime related named entities,deep learning, neural network, LSTM, CNN, NER, NLP