Abstract
This article describes a method and tool to identify expert translators in an on-demand translation service. We start from existing efforts on expert retrieval and factor in additional parameters based on the real-world scenario of the task. The system first identifies topical expertise using an aggregation function over relevance scores of previously translated documents by each translator, and then a learning to rank method to factor in non-topical relevance factors that are part of the decision-making process of the user, such as price and duration of translation. We test the system on a manually created test collection and show that the method is able to effectively support the user in selecting the best translator.
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References
Grefenstette, G., Wilber, L.: Search Based Applications. Morgan & Claypool Publishers (2011)
Balog, K., Bogers, T., Azzopardi, L., de Rijke, M., van den Bosch, A.: Broad expertise retrieval in sparse data environments. In: Proc. of SIGIR (2007)
Balog, K., Fang, Y., de Rijke, M., Serdyukov, P., Si., L.: Expertise retrieval. Foundations and Trends in Information Retrieval 6 (2012)
Deng, H., King, I., Lyu, M.R.: Enhanced models for expertise retrieval using community-aware strategies. IEEE Transactions on Systems Man and Cybernetics Part B: Cybernetics (2012)
Cao, Y., Liu, J., Bao, S., Li, H.: Research on expert search at enterprise track of trec 2005. In: Proc. of TREC (2005)
Macdonald, C., Ounis, I.: Learning Models for Ranking Aggregates. In: Clough, P., Foley, C., Gurrin, C., Jones, G.J.F., Kraaij, W., Lee, H., Mudoch, V. (eds.) ECIR 2011. LNCS, vol. 6611, pp. 517–529. Springer, Heidelberg (2011)
Hang, L.I.: A short introduction to learning to rank. Transactions on Information and Systems (2011)
Cummins, R., Lalmas, M., O’Riordan, C.: Learning aggregation functions for expert search. In: Proc. of ECAI (2010)
Macdonald, C., Ounis, I.: Voting for candidates: adapting data fusion techniques for an expert search task. In: Proc. of CIKM (2006)
Lie, T.Y.: Learning to rank for information retrieval. Foundations and Trends in Information Retrieval. Springer (2011)
Burges, C., Shaked, T., Renshaw, E., Lazier, A., Deeds, M., Hamilton, N., Hullender, G.: Learning to rank using gradient descent. In: Proc. of ICML (2005)
Freund, Y., Iyer, R., Schapire, R.E., Singer, Y.: An efficient boosting algorithm for combining preferences (1998)
Burges, C.C.J., Ragno, R., Le, V.Q.: Learning to rank with nonsmooth cost functions. MIT Press (2006)
Wu, Q., Burges, C.J.C., Svore, K.M., Gao, J.: Adapting boosting for information retrieval measures. Springer Science (2009)
Xu, J., Li, H.: Adarank: A boosting algorithm for information retrieval. In: Procs of SIGIR (2007)
Cao, Z., Qin, T., Liu, T.Y., Tsai, M.F., Li, H.: Learning to rank: From pairwise approach to listwise approach. In: Procs of ICML (2007)
Macdonald, C., Santos, R.L., Ounis, I.: The whens and hows of learning to rank for web search. Inf. Retr. 16 (2013)
Chapelle, O., Zhang, Y.: Expected reciprocal rank for graded relevance. In: Proc. of CIKM (2009)
Craswell, N., Zoeter, O., Taylor, M., Ramsey, B.: An experimental comparison of click position-bias models. In: Proc. of WSDM (2008)
Büttcher, S., Clarke, C.L.A., Yeung, P.C.K., et al.: Reliable information retrieval evaluation with incomplete and biased judgements (2007)
Best, D.J., Roberts, D.E.: Algorithm as 89: The upper tail probabilities of spearman’s rho. Journal of the Royal Statistical Society. Series C (Applied Statistics) 24 (1975)
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Rekabsaz, N., Lupu, M. (2014). A Real-World Framework for Translator as Expert Retrieval. In: Kanoulas, E., et al. Information Access Evaluation. Multilinguality, Multimodality, and Interaction. CLEF 2014. Lecture Notes in Computer Science, vol 8685. Springer, Cham. https://doi.org/10.1007/978-3-319-11382-1_14
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DOI: https://doi.org/10.1007/978-3-319-11382-1_14
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11381-4
Online ISBN: 978-3-319-11382-1
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