In this paper, we describe the construction of TeKnowbase, a knowledge-base of technical concepts in computer science. Our main information sources are technical websites such as Webopedia and Techtarget as well as Wikipedia and online textbooks. We divide the knowledge-base construction problem into two parts -- the acquisition of entities and the extraction of relationships among these entities. Our knowledge-base consists of approximately 100,000 triples. We conducted an evaluation on a sample of triples and report an accuracy of a little over 90\%. We additionally conducted classification experiments on StackOverflow data with features from TeKnowbase and achieved improved classification accuracy.
@article{arxiv.1612.04988,
title = {TeKnowbase: Towards Construction of a Knowledge-base of Technical Concepts},
author = {Prajna Upadhyay and Tanuma Patra and Ashwini Purkar and Maya Ramanath},
journal= {arXiv preprint arXiv:1612.04988},
year = {2016}
}