Abstract
Many text documents are temporal in nature, i.e., the contents of the document can be mapped to a specific time period. For example, a news article about the Kargil War can be mapped to the year 1999. Identifying this time period associated with the document can be useful for various downstream applications such as document reasoning, temporal information retrieval, etc. In this work, we propose a graph based approach for estimating the focus time of a document. The idea is to treat documents and years as nodes which are connected by intermediate Wikipedia concepts related to them. The focus year of a document can then be identified as the year which has the maximum influence over the document computed using the flow between the year node and the document node through all intermediate Wikipedia concept nodes. We evaluate our approach on two different datasets which were curated as a part of this work and show that our approach outperforms a state of the art method for estimating document focus time.
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Alonso, O., Strötgen, J., Baeza-Yates, R.A., Gertz, M.: Temporal information retrieval. TWAW 11, 1–8 (2011)
Berberich, K., Bedathur, S., Alonso, O., Weikum, G.: A language modeling approach for temporal information needs. In: Gurrin, C., He, Y., Kazai, G., Kruschwitz, U., Little, S., Roelleke, T., Rüger, S., van Rijsbergen, K. (eds.) ECIR 2010. LNCS, vol. 5993, pp. 13–25. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-12275-0_5
Gabrilovich, E., Markovitch, S.: Computing semantic relatedness using wikipedia-based explicit semantic analysis. In: IJCAI, vol. 7, pp. 1606–1611 (2007)
Jatowt, A., Au Yeung, C.-M., Tanaka, K.: Estimating document focus time. In: CIKM, pp. 2273–2278. ACM (2013)
Joho, H., Jatowt, A., Roi, B.: A survey of temporal web search experience. In: WWW, pp. 1101–1108. ACM (2013)
Jones, R., Diaz, F.: Temporal profiles of queries. ACM Trans. Inf. Syst. (TOIS) 25(3), 14 (2007)
de Jong, F.M.G., Rode, H., Hiemstra, D.: Temporal Language Models for the Disclosure of Historical Text. Royal Netherlands Academy of Arts and Sciences, Amsterdam (2005)
Kanhabua, N., Nørvåg, K.: Improving temporal language models for determining time of non-timestamped documents. In: Christensen-Dalsgaard, B., Castelli, D., Ammitzbøll Jurik, B., Lippincott, J. (eds.) ECDL 2008. LNCS, vol. 5173, pp. 358–370. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-87599-4_37
Kanhabua, N., Nørvåg, K.: Using temporal language models for document dating. In: Buntine, W., Grobelnik, M., Mladenić, D., Shawe-Taylor, J. (eds.) ECML PKDD 2009. LNCS (LNAI), vol. 5782, pp. 738–741. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-04174-7_53
Kanhabua, N., Nørvåg, K.: Determining time of queries for re-ranking search results. In: Lalmas, M., Jose, J., Rauber, A., Sebastiani, F., Frommholz, I. (eds.) ECDL 2010. LNCS, vol. 6273, pp. 261–272. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-15464-5_27
Kotsakos, D., Lappas, T., Kotzias, D., Gunopulos, D., Kanhabua, N., and Nørvåg, K.: A burstiness-aware approach for document dating. In: Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval, pp. 1003–1006. ACM (2014)
Lappas, T., Arai, B., Platakis, M., Kotsakos, D., Gunopulos, D.: On burstiness-aware search for document sequences. In: Proceedings of the 15th ACM SIGKDD, pp. 477–486. ACM (2009)
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Shrivastava, S., Khapra, M., Chakraborti, S. (2017). A Concept Driven Graph Based Approach for Estimating the Focus Time of a Document. In: Ghosh, A., Pal, R., Prasath, R. (eds) Mining Intelligence and Knowledge Exploration. MIKE 2017. Lecture Notes in Computer Science(), vol 10682. Springer, Cham. https://doi.org/10.1007/978-3-319-71928-3_25
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DOI: https://doi.org/10.1007/978-3-319-71928-3_25
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