Academic Journal
Expert as a service: Software expert recommendation via knowledge domain embeddings in stack overflow
| العنوان: | Expert as a service: Software expert recommendation via knowledge domain embeddings in stack overflow |
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| المؤلفون: | HUANG, Chaoran, YAO, Lina, WANG, Xianzhi, BENATALLAH, Boualem, SHENG, Quan Z. |
| المصدر: | Research Collection School Of Computing and Information Systems |
| بيانات النشر: | Institutional Knowledge at Singapore Management University |
| سنة النشر: | 2017 |
| المجموعة: | Institutional Knowledge (InK) at Singapore Management University |
| مصطلحات موضوعية: | Expert as a Service, Expertise finding, Knowledge discovery, Question answering, Stack Overflow, Cluster analysis, Computer programming, Data mining, Factorization, Graphic methods, Matrix algebra, Natural language processing systems, Semantics, Websites, Collaborative network, Expert recommendations, Graph-based clustering, Matrix factorizations, Web services, Programming Languages and Compilers, Software Engineering |
| الوصف: | Question answering (Q&A) communities have gained momentum recently as an effective means of knowledge sharing over the crowds, where many users are experts in the real-world and can make quality contributions in certain domains or technologies. Although the massive user-generated Q&A data present a valuable source of human knowledge, a related challenging issue is how to find those expert users effectively. In this paper, we propose a framework for finding such experts in a collaborative network. Accredited with recent works on distributed word representations, we are able to summarize text chunks from the semantics perspective and infer knowledge domains by clustering pre-trained word vectors. In particular, we exploit a graph-based clustering method for knowledge domain extraction and discern the shared latent factors using matrix factorization techniques. The proposed clustering method features requiring no post-processing of clustering indicators and the matrix factorization method is combined with the semantic similarity of the historical answers to conduct expertise ranking of users given a query. We use Stack Overflow, a website with a large group of users and a large number of posts on topics related to computer programming, to evaluate the proposed approach and conduct extensively experiments to show the effectiveness of our approach. |
| نوع الوثيقة: | text |
| اللغة: | English |
| Relation: | https://ink.library.smu.edu.sg/sis_research/4046 |
| DOI: | 10.1109/ICWS.2017.122 |
| الاتاحة: | https://ink.library.smu.edu.sg/sis_research/4046 https://doi.org/10.1109/ICWS.2017.122 |
| رقم الانضمام: | edsbas.78908AA8 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1109/ICWS.2017.122 |
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