TeKnowbase: Towards Construction of a Knowledge-base of Technical Concepts
Prajna Upadhyay, Tanuma Patra, Ashwini Purkar, Maya Ramanath

TL;DR
TeKnowbase is a large, accurate knowledge-base of computer science concepts built from online sources, improving technical concept classification tasks.
Contribution
This work introduces TeKnowbase, a comprehensive knowledge-base of technical concepts with high accuracy, constructed from multiple online sources, and demonstrates its utility in classification tasks.
Findings
Knowledge-base contains approximately 100,000 triples.
Achieved over 90% accuracy in triple evaluation.
Improved classification accuracy on StackOverflow data.
Abstract
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.
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Taxonomy
TopicsAdvanced Text Analysis Techniques · Topic Modeling · Natural Language Processing Techniques
