Context injection in expert finding
Resumo
Expert finding is a subject of research in information retrieval and, often, is taken to mean expertise retrieval within a specific organization. The task involves finding an expert on a given topic of interest. Even though there are several proposals in the literature, they do not consider the context in which the given expertise is bound. This paper introduces an approach to inject context into existing expertise evidence based on data extracted from the evidence. Our motivation is to provide context when describing the expertise associated with a candidate expert, allowing a user to understand the results better and choose the best candidate for the task.
Palavras-chave:
Expert finding, expertise retrieval, context, data retrieval.
Referências
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Manish Bhanu and Joydeep Chandra. 2016. Exploiting response patterns for identifying topical experts in StackOverflow. In 2016 Eleventh International Conference on Digital Information Management (ICDIM). 139–144. https://doi.org/10.1109/ICDIM.2016.7829790
Hung-Hsuan Chen, Pucktada Treeratpituk, Prasenjit Mitra, and Clyde Lee Giles. 2013. CSSeer: An Expert Recommendation System Based on CiteseerX. In Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries (Indianapolis, Indiana, USA) (JCDL ’13). ACM, New York, NY, USA, 381–382. https://doi.org/10.1145/2467696.2467750
Mohamed Fayad and Douglas Clark Schmidt. 1997. Object-Oriented Application Frameworks. Commun. ACM 40, 10 (oct 1997), 32–38. https://doi.org/10.1145/262793.262798
Rodrigo Gonçalves and Carina Friedrich Dorneles. 2019. Automated Expertise Retrieval: A Taxonomy-Based Survey and Open Issues. ACM Comput. Surv. 52, 5, Article 96 (Sept. 2019), 30 pages. https://doi.org/10.1145/3331000
Glen Jeh and Jennifer Widom. 2002. SimRank: A Measure of Structural-Context Similarity. In Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(Edmonton, Alberta, Canada) (KDD ’02). Association for Computing Machinery, New York, NY, USA, 538–543. https://doi.org/10.1145/775047.775126
Yanyan Li, Shaoqian Ma, Yonghe Zhang, and Ronghuai Huang. 2012. Expertise Network Discovery via Topic and Link Analysis in Online Communities. In 2012 IEEE 12th International Conference on Advanced Learning Technologies. 311–315. https://doi.org/10.1109/ICALT.2012.80
Shangsong Liang and Maarten de Rijke. 2016. Formal language models for finding groups of experts. Information Processing and Management 52, 4 (2016), 529–549. https://doi.org/10.1016/j.ipm.2015.11.005
Dong Liu, Li Wang, Jianhua Zheng, Ke Ning, and Liang-Jie Zhang. 2013. Influence Analysis Based Expert Finding Model and Its Applications in Enterprise Social Network. In 2013 IEEE International Conference on Services Computing. 368–375. https://doi.org/10.1109/SCC.2013.72
Jingyuan Liu, Debing Liu, Xingyu Yan, Li Dong, Ting Zeng, Yutao Zhang, and Jie Tang. 2014. AMiner-mini: A People Search Engine for University. In Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management (Shanghai, China) (CIKM ’14). ACM, New York, NY, USA, 2069–2071. https://doi.org/10.1145/2661829.2661852
Bertrand Meyer. 2007. Contract-Driven Development. In Fundamental Approaches to Software Engineering, Matthew B. Dwyer and Antónia Lopes (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 11–11. https://doi.org/10.1007/978-3-540-71289-3
Mahmood Neshati, Seyyed Hadi Hashemi, and Hamid Beigy. 2014. Expertise finding in bibliographic network: Topic dominance learning approach. IEEE Transactions on Cybernetics 44, 12 (2014), 2646–2657. https://doi.org/10.1109/TCYB.2014.2312614
Mahmood Neshati, Djoerd Hiemstra, Ehsaneddin Asgari, and Hamid Beigy. 2014. Integration of scientific and social networks. World Wide Web 17, 5 (2014), 1051–1079. https://doi.org/10.1007/s11280-013-0229-1
Aditya Pal. 2015. Discovering Experts Across Multiple Domains. In Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (Santiago, Chile) (SIGIR ’15). ACM, New York, NY, USA, 923–926. https://doi.org/10.1145/2766462.2767774
Tao Peng, Delong Zhang, Xiaoming Liu, Shang Wang, and Wanli Zuo. 2013. Central Author Mining from Co-authorship Network. In 2013 Sixth International Symposium on Computational Intelligence and Design, Vol. 1. 228–232. https://doi.org/10.1109/ISCID.2013.64
Ravikarn Punnarut and Gridaphat Sriharee. 2010. A Researcher Expertise Search System Using Ontology-based Data Mining. In Proceedings of the Seventh Asia-Pacific Conference on Conceptual Modelling - Volume 110(Brisbane, Australia) (APCCM ’10). Australian Computer Society, Inc., Darlinghurst, Australia, Australia, 71–78. http://dl.acm.org/citation.cfm?id=1862330.1862341
Bahar Sateli, Felicitas Löffler, Birgitta König-Ries, and René Witte. 2017. ScholarLens: Extracting competences from research publications for the automatic generation of semantic user profiles. PeerJ Computer Science 2017 (2017). Issue 7. https://doi.org/10.7717/peerj-cs.121
Quan Thanh Tho, Siu Cheng Hui, and Alvis Fong. 2003. A Web mining approach for finding expertise in research areas. In Proceedings. 2003 International Conference on Cyberworlds. 310–317. https://doi.org/10.1109/CYBER.2003.1253470
Cornelis Joost van Rijsbergen. 1979. Information Retrieval(2nd ed.). Butterworth-Heinemann. https://doi.org/10.1002/asi.4630300621
Manish Bhanu and Joydeep Chandra. 2016. Exploiting response patterns for identifying topical experts in StackOverflow. In 2016 Eleventh International Conference on Digital Information Management (ICDIM). 139–144. https://doi.org/10.1109/ICDIM.2016.7829790
Hung-Hsuan Chen, Pucktada Treeratpituk, Prasenjit Mitra, and Clyde Lee Giles. 2013. CSSeer: An Expert Recommendation System Based on CiteseerX. In Proceedings of the 13th ACM/IEEE-CS Joint Conference on Digital Libraries (Indianapolis, Indiana, USA) (JCDL ’13). ACM, New York, NY, USA, 381–382. https://doi.org/10.1145/2467696.2467750
Mohamed Fayad and Douglas Clark Schmidt. 1997. Object-Oriented Application Frameworks. Commun. ACM 40, 10 (oct 1997), 32–38. https://doi.org/10.1145/262793.262798
Rodrigo Gonçalves and Carina Friedrich Dorneles. 2019. Automated Expertise Retrieval: A Taxonomy-Based Survey and Open Issues. ACM Comput. Surv. 52, 5, Article 96 (Sept. 2019), 30 pages. https://doi.org/10.1145/3331000
Glen Jeh and Jennifer Widom. 2002. SimRank: A Measure of Structural-Context Similarity. In Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(Edmonton, Alberta, Canada) (KDD ’02). Association for Computing Machinery, New York, NY, USA, 538–543. https://doi.org/10.1145/775047.775126
Yanyan Li, Shaoqian Ma, Yonghe Zhang, and Ronghuai Huang. 2012. Expertise Network Discovery via Topic and Link Analysis in Online Communities. In 2012 IEEE 12th International Conference on Advanced Learning Technologies. 311–315. https://doi.org/10.1109/ICALT.2012.80
Shangsong Liang and Maarten de Rijke. 2016. Formal language models for finding groups of experts. Information Processing and Management 52, 4 (2016), 529–549. https://doi.org/10.1016/j.ipm.2015.11.005
Dong Liu, Li Wang, Jianhua Zheng, Ke Ning, and Liang-Jie Zhang. 2013. Influence Analysis Based Expert Finding Model and Its Applications in Enterprise Social Network. In 2013 IEEE International Conference on Services Computing. 368–375. https://doi.org/10.1109/SCC.2013.72
Jingyuan Liu, Debing Liu, Xingyu Yan, Li Dong, Ting Zeng, Yutao Zhang, and Jie Tang. 2014. AMiner-mini: A People Search Engine for University. In Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management (Shanghai, China) (CIKM ’14). ACM, New York, NY, USA, 2069–2071. https://doi.org/10.1145/2661829.2661852
Bertrand Meyer. 2007. Contract-Driven Development. In Fundamental Approaches to Software Engineering, Matthew B. Dwyer and Antónia Lopes (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 11–11. https://doi.org/10.1007/978-3-540-71289-3
Mahmood Neshati, Seyyed Hadi Hashemi, and Hamid Beigy. 2014. Expertise finding in bibliographic network: Topic dominance learning approach. IEEE Transactions on Cybernetics 44, 12 (2014), 2646–2657. https://doi.org/10.1109/TCYB.2014.2312614
Mahmood Neshati, Djoerd Hiemstra, Ehsaneddin Asgari, and Hamid Beigy. 2014. Integration of scientific and social networks. World Wide Web 17, 5 (2014), 1051–1079. https://doi.org/10.1007/s11280-013-0229-1
Aditya Pal. 2015. Discovering Experts Across Multiple Domains. In Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (Santiago, Chile) (SIGIR ’15). ACM, New York, NY, USA, 923–926. https://doi.org/10.1145/2766462.2767774
Tao Peng, Delong Zhang, Xiaoming Liu, Shang Wang, and Wanli Zuo. 2013. Central Author Mining from Co-authorship Network. In 2013 Sixth International Symposium on Computational Intelligence and Design, Vol. 1. 228–232. https://doi.org/10.1109/ISCID.2013.64
Ravikarn Punnarut and Gridaphat Sriharee. 2010. A Researcher Expertise Search System Using Ontology-based Data Mining. In Proceedings of the Seventh Asia-Pacific Conference on Conceptual Modelling - Volume 110(Brisbane, Australia) (APCCM ’10). Australian Computer Society, Inc., Darlinghurst, Australia, Australia, 71–78. http://dl.acm.org/citation.cfm?id=1862330.1862341
Bahar Sateli, Felicitas Löffler, Birgitta König-Ries, and René Witte. 2017. ScholarLens: Extracting competences from research publications for the automatic generation of semantic user profiles. PeerJ Computer Science 2017 (2017). Issue 7. https://doi.org/10.7717/peerj-cs.121
Quan Thanh Tho, Siu Cheng Hui, and Alvis Fong. 2003. A Web mining approach for finding expertise in research areas. In Proceedings. 2003 International Conference on Cyberworlds. 310–317. https://doi.org/10.1109/CYBER.2003.1253470
Cornelis Joost van Rijsbergen. 1979. Information Retrieval(2nd ed.). Butterworth-Heinemann. https://doi.org/10.1002/asi.4630300621
Publicado
07/11/2022
Como Citar
GONÇALVES, Rodrigo; DORNELES, Carina Friedrich.
Context injection in expert finding. In: BRAZILIAN SYMPOSIUM ON MULTIMEDIA AND THE WEB (WEBMEDIA), 28. , 2022, Curitiba.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 179-188.
