Abstract
Nowadays data sources are producing huge amount of data everywhere namely news data, wikis, web crawlers and many other databases, data needs to be analyze and exploited to obtain the required information to build several knowledge databases. In this context time is an essential component of information space and it is a real phenomenon which makes a continuous change through which we live. The information which is associated with time is termed as temporal information and the process of identifying and retrieving times are called as temporal information extraction (TIE). The temporal information extraction is useful in many natural language processing (NLP) applications like information extraction for generating better text summaries and temporal question answering (Q.A) systems for time related searches, and information retrievals etc. Times are also useful to order the events in the text, the ordering can be from the past through the present into the future and this will helpful to measure the durations of an event occurrence and find outs the relation between them. In this paper we present our work for extraction of various forms of times from natural language by using pattern rules. The results obtained from the experiments found to have better precision value when compared with existing methods.
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Guda, V., Sanampudi, S.K. (2017). Pattern Based Extraction of Times from Natural Language Text. In: Saini, H., Sayal, R., Rawat, S. (eds) Innovations in Computer Science and Engineering. Lecture Notes in Networks and Systems, vol 8. Springer, Singapore. https://doi.org/10.1007/978-981-10-3818-1_6
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DOI: https://doi.org/10.1007/978-981-10-3818-1_6
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