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2022 | OriginalPaper | Buchkapitel

Expert Finding in Legal Community Question Answering

verfasst von : Arian Askari, Suzan Verberne, Gabriella Pasi

Erschienen in: Advances in Information Retrieval

Verlag: Springer International Publishing

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Abstract

Expert finding has been well-studied in community question answering (QA) systems in various domains. However, none of these studies addresses expert finding in the legal domain, where the goal is for citizens to find lawyers based on their expertise. In the legal domain, there is a large knowledge gap between the experts and the searchers, and the content on the legal QA websites consist of a combination formal and informal communication. In this paper, we propose methods for generating query-dependent textual profiles for lawyers covering several aspects including sentiment, comments, and recency. We combine query-dependent profiles with existing expert finding methods. Our experiments are conducted on a novel dataset gathered from an online legal QA service. We discovered that taking into account different lawyer profile aspects improves the best baseline model. We make our dataset publicly available for future work.

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Vorheriges Kapitel Passage Retrieval on Structured Documents Using Graph Attention Networks

Nächstes Kapitel Towards Building Economic Models of Conversational Search

The data and code is available on https://github.com/EF_in_Legal_CQA.

Althammer, S., Askari, A., Verberne, S., Hanbury, A.: DoSSIER@ COLIEE 2021: leveraging dense retrieval and summarization-based re-ranking for case law retrieval. arXiv preprint arXiv:2108.03937 (2021)

Bailey, P., De Vries, A.P., Craswell, N., Soboroff, I.: Overview of the TREC 2007 enterprise track. In: TREC. Citeseer (2007)

Balog, K., Azzopardi, L., de Rijke, M.: A language modeling framework for expert finding. Inf. Process. Manage. 45(1), 1–19 (2009)CrossRef

Balog, K., Fang, Y., De Rijke, M., Serdyukov, P., Si, L.: Expertise retrieval. Found. Trends Inf. Retrieval 6(2–3), 127–256 (2012)CrossRef

Balog, K., Thomas, P., Craswell, N., Soboroff, I., Bailey, P., De Vries, A.P.: Overview of the TREC 2008 enterprise track. Amsterdam Univ (Netherlands), Tech. rep. (2008)

Craswell, N., De Vries, A.P., Soboroff, I.: Overview of the TREC 2005 enterprise track. In: TREC, vol. 5, pp. 1–7 (2005)

Dargahi Nobari, A., Sotudeh Gharebagh, S., Neshati, M.: Skill translation models in expert finding. In: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1057–1060 (2017)

Dehghan, M., Abin, A.A., Neshati, M.: An improvement in the quality of expert finding in community question answering networks. Decis. Supp. Syst. 139, 113425 (2020)

van Dijk, D., Tsagkias, M., de Rijke, M.: Early detection of topical expertise in community question answering. In: Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 995–998 (2015)

10.

Fu, J., Li, Y., Zhang, Q., Wu, Q., Ma, R., Huang, X., Jiang, Y.G.: Recurrent memory reasoning network for expert finding in community question answering. In: Proceedings of the 13th International Conference on Web Search and Data Mining, pp. 187–195 (2020)

11.

Guo, J., Xu, S., Bao, S., Yu, Y.: Tapping on the potential of Q & A community by recommending answer providers. In: Proceedings of the 17th ACM Conference on Information and Knowledge Management, pp. 921–930 (2008)

12.

Hutto, C., Gilbert, E.: Vader: a parsimonious rule-based model for sentiment analysis of social media text. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 8 (2014)

13.

Li, G., et al.: Misinformation-oriented expert finding in social networks. World Wide Web 23(2), 693–714 (2019). https://doi.org/10.1007/s11280-019-00717-6CrossRef

14.

Liu, X., Ye, S., Li, X., Luo, Y., Rao, Y.: ZhihuRank: a topic-sensitive expert finding algorithm in community question answering websites. In: Li, F., Klamma, R., Laanpere, M., Zhang, J., Manjôn, B., Lau, R. (eds.) Advances in Web-Based Learning – ICWL 2015. ICWL 2015. Lecture Notes in Computer Science, vol. 9412. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25515-6_15

15.

MacAvaney, S., Yates, A., Cohan, A., Goharian, N.: CEDR: contextualized embeddings for document ranking. In: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1101–1104 (2019)

16.

Neshati, M., Hashemi, S.H., Beigy, H.: Expertise finding in bibliographic network: topic dominance learning approach. IEEE Trans. Cybern. 44(12), 2646–2657 (2014)CrossRef

17.

Neshati, M., Hiemstra, D., Asgari, E., Beigy, H.: Integration of scientific and social networks. World Wide Web 17(5), 1051–1079 (2013). https://doi.org/10.1007/s11280-013-0229-1CrossRef

18.

Nikzad-Khasmakhi, N., Balafar, M., Feizi-Derakhshi, M.R., Motamed, C.: Berters: multimodal representation learning for expert recommendation system with transformers and graph embeddings. Chaos, Solitons Fractals 151, 111260 (2021)

19.

Pekaar, K.A., van der Linden, D., Bakker, A.B., Born, M.P.: Emotional intelligence and job performance: the role of enactment and focus on others’ emotions. Human Perf. 30(2–3), 135–153 (2017)CrossRef

20.

Riahi, F., Zolaktaf, Z., Shafiei, M., Milios, E.: Finding expert users in community question answering. In: Proceedings of the 21st International Conference on World Wide Web, pp. 791–798 (2012)

21.

Rostami, P., Neshati, M.: Intern retrieval from community question answering websites: a new variation of expert finding problem. Expert Syst. Appl. 181, 115044 (2021)

22.

Sandefur, R.L.: Elements of professional expertise: understanding relational and substantive expertise through lawyers’ impact. Am. Soc. Rev. 80(5), 909–933 (2015)CrossRef

23.

Shanahan, C.F., Carpenter, A.E., Mark, A.: Lawyers, power, and strategic expertise. Denv. L. Rev. 93, 469 (2015)

24.

Soboroff, I., de Vries, A.P., Craswell, N., et al.: Overview of the TREC 2006 enterprise track. In: TREC, vol. 6, pp. 1–20 (2006)

25.

Torkzadeh Mahani, N., Dehghani, M., Mirian, M.S., Shakery, A., Taheri, K.: Expert finding by the dempster-shafer theory for evidence combination. Expert Syst. 35(1), e12231 (2018)

26.

Wang, Q., Ma, J., Liao, X., Du, W.: A context-aware researcher recommendation system for university-industry collaboration on R&D projects. Decis. Support Syst. 103, 46–57 (2017)CrossRef

27.

Xu, F., Ji, Z., Wang, B.: Dual role model for question recommendation in community question answering. In: Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 771–780 (2012)

28.

Yang, J., Tao, K., Bozzon, A., Houben, G.J.: Sparrows and owls: characterisation of expert behaviour in stackoverflow. In: Dimitrova, V., Kuflik, T., Chin, D., Ricci, F., Dolog, P., Houben, G.J. (eds.) User Modeling, Adaptation, and Personalization. UMAP 2014. Lecture Notes in Computer Science, vol. 8538. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-08786-3_23

29.

Yang, L., Qiu, M., Gottipati, S., Zhu, F., Jiang, J., Sun, H., Chen, Z.: CQARank: jointly model topics and expertise in community question answering. In: Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp. 99–108 (2013)

30.

Zhou, G., Zhao, J., He, T., Wu, W.: An empirical study of topic-sensitive probabilistic model for expert finding in question answer communities. Knowl.-Based Syst. 66, 136–145 (2014)CrossRef

Titel: Expert Finding in Legal Community Question Answering
verfasst von: Arian Askari
Suzan Verberne
Gabriella Pasi
Verlag: Springer International Publishing
Buch: Advances in Information Retrieval
Print ISBN: 978-3-030-99738-0

Electronic ISBN: 978-3-030-99739-7

Copyright-Jahr: 2022
DOI: https://doi.org/10.1007/978-3-030-99739-7_3

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