請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/15970
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 鄭卜壬 | |
dc.contributor.author | Ching-Han Tzou | en |
dc.contributor.author | 鄒京翰 | zh_TW |
dc.date.accessioned | 2021-06-07T17:56:47Z | - |
dc.date.copyright | 2012-08-20 | |
dc.date.issued | 2012 | |
dc.date.submitted | 2012-08-14 | |
dc.identifier.citation | [1] Bernard J. Jansen, Amanda Spink, Judy Bateman, and Tefko Saracevic, “Real Life Information Retrieval: A Study of User Queries on the Web,” SIGIR Forum, vol. 32, no. 1, pp. 5–17, Apr. 1998.
[2] Jaime Carbonell and Jade Goldstein, “The Use of MMR, Diversity-based Reranking for Reordering Documents and Producing Summaries,” in Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval, New York, NY, USA, 1998, SIGIR ’98, pp. 335–336, ACM. [3] Filip Radlinski and Susan Dumais, “Improving Personalized Web Search Using Result Diversification,” in Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, New York, NY, USA, 2006, SIGIR ’06, pp. 691–692, ACM. [4] Jesse Funaro, “Diversity as an Objective in Informational Retrieval Experiments with a Navigation System,” M.S. thesis, Department of Computer Science, Brown University, Providence, RI, USA, 2005. [5] Charles L A Clarke, Maheedhar Kolla, Gordon V Cormack, Olga Vechtomova, Azin Ashkan, Stefan Buttcher, and Ian MacKinnon, “Novelty and Diversity in Information Retrieval Evaluation,” in International Conference on Research and Development in Information Retrieval, New York, New York, USA, 2008, University of Waterloo, pp. 659–666, ACM Press. [6] Rakesh Agrawal, Sreenivas Gollapudi, Alan Halverson, and Samuel Ieong, “Diversifying Search Results,” in Web Search and Data Mining, New York, New York, USA, Feb. 2009, Microsoft Research, WSDM ’09, pp. 5–14, ACM Press. [7] Charles L A Clarke, Nick Craswell, and Ian Soboroff, “Overview of the TREC 2009 Web Track,” in Proceedings of the 18th Text REtrieval Conference. 2009, TREC ’09, National Institute of Standards and Technology (NIST). [8] Rodrygo L T Santos, Craig Macdonald, and Iadh Ounis, “Exploiting Query Reformulations for Web Search Result Diversification,” in International World Wide Web Conferences, New York, New York, USA, 2010, WWW ’10, pp. 881–890, ACM Press. [9] Rodrygo L T Santos, Craig Macdonald, and Iadh Ounis, “Intent-Aware Search Result Diversification,” in International Conference on Research and Development in Information Retrieval, New York, New York, USA, 2011, pp. 595–604, ACM Press. [10] Wikipedia, “Marginal utility — Wikipedia, the free encyclopedia,” http://en. wikipedia.org/wiki/Marginal_utility, Jul 2012, [Online resource; accessed 28-July-2012]. [11] Wei Zheng and Hui Fang, “A Comparative Study of Search Result Diversification Methods,” in International Workshop on Diversity in Document Retrieval, 2011, DDR ’11, pp. 55–62. [12] Dawei Yin, Zhenzhen Xue, Xiaoguang Qi, and Brian D Davison, “Diversifying Search Results with Popular Subtopics,” in Text REtrieval Conference, June 2009, TREC ’09, pp. 1–9. [13] ChengXiang Zhai, William W Cohen, and John Lafferty, “Beyond Independent Relevance: Methods and Evaluation Metrics for Subtopic Retrieval,” in International Conference on Research and Development in Information Retrieval. July 2003, pp. 10–17, ACM Press. [14] Robert V Hogg and Elliot A Tanis, Probability and Statistical Inference, chapter 2, pp. 90–97, Pearson Education, Inc., 7e edition, 2006. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/15970 | - |
dc.description.abstract | 為了提高同時滿足不同使用者的機率,搜尋結果多樣化試圖讓搜尋結果適度涵蓋搜尋關鍵字的各種意圖與面相,亦即子議題。隨著網路資訊量逐年成長及冗餘資訊的增加,搜尋結果多樣化的地位愈趨重要。近年來愈來愈多研究者投入此一研究,相關的會議與競賽也十分熱絡。本研究詳細分析了數個現有的搜尋結果多樣化方案及相關的效能評估方法,認為子議題新穎度為目前研究的重點。針對搜尋結果多樣化,作者提出了一個新的子議題新穎度模型,藉由一個二項分配機率模型模擬使用者掃描搜尋結果、尋找有用資訊之行為。透過預測使用者對一特定子議題的需求,在閱讀相關文件後所得到的滿意度,可以進一步推測子議題的新穎度變化。
本研究使用文字檢索會議中搜尋結果多樣性競賽之資料集,並與現有方法比較。實驗結果顯示本研究所提出之新穎度二項機率模型能夠進一步提昇目前一名列前茅之現有方法 xQuAD 的效能。此外,實驗結果亦指出本方法具有能夠適應各種不同性質搜尋詞的能力,可以針對不同搜尋詞提出最適宜的新穎度估計方法。 | zh_TW |
dc.description.abstract | Search result diversification aims to satisfy different types of user at the same time by providing a proper mixture of interpretations and aspects of a single query string, i.e. query subtopics. As the Web grows steadily, it has been more and more important today; competitions have been hold and researches have been carried out in recent years. In this thesis, with several state-of-the-art methods and evaluations being studied thoroughly and observations made, a new subtopic novelty model that improves diversification effectiveness by modeling user satisfaction with a binomial random process is proposed. It models subtopic novelty by estimating the satisfaction a user attains when he or she skims over a result document.
Results of experiments on the TREC Diversity Task competition dataset show that the proposed novelty model further improves one of the most dominating method today, namely xQuAD. Experiments show that it has the capability to be fine-tuned for queries with different attributes as well. | en |
dc.description.provenance | Made available in DSpace on 2021-06-07T17:56:47Z (GMT). No. of bitstreams: 1 ntu-101-R98922113-1.pdf: 2411457 bytes, checksum: 8ede3d236aad869cb878f3f6a8a07c85 (MD5) Previous issue date: 2012 | en |
dc.description.tableofcontents | 口試委員會審定書 .. i
誌謝 .. ii 中文摘要 .. iii 英文摘要 .. iv 目錄 .. v 圖目錄 .. viii 表目錄 .. x 演算法目錄 .. xi Chapter 1 Introduction .. 1 1.1 Background .. 1 1.2 Motivation .. 5 1.3 Problem Definition and Proposed Solutions .. 7 1.4 Thesis Organization .. 8 Chapter 2 Related Works .. 9 2.1 An Influential Early Work — MMR .. 9 2.2 Explicit Subtopic Approaches .. 11 2.2.1 WUME .. 12 2.2.2 xQuAD .. 13 2.3 Evaluating Diversity .. 15 2.3.1 Intent-aware Evaluations .. 15 2.3.2 α-nDCG .. 17 2.4 Chapter Summarization .. 19 Chapter 3 Ovservations and Trials .. 20 3.1 Ineffectiveness of xQuAD’s Novelty Estimation .. 21 3.2 Usefulness of Subtopic Novelty .. 23 3.3 Direct Usage of α-nDCG’s Freshness .. 24 3.4 Chapter Conclusion .. 26 Chapter 4 Methodology .. 27 4.1 Intuition .. 27 4.2 Binomial Probability Distribution .. 28 4.3 Properties of the Novelty Model .. 30 4.4 Methodology Summarization .. 31 Chapter 5 Expreimants and Analyses .. 32 5.1 Experiment Setup .. 32 5.2 Model Effectiveness and Parameter Selection .. 35 5.2.1 The Model’s Behavior by Different Parameters .. 36 5.3 Per-subtopic Parameters .. 42 5.4 Using Another Training Dataset .. 43 5.5 Discussion — Degeneration to xQuAD .. 45 5.6 Chapter Summarization .. 47 Chapter 6 Conclusion and Future Works .. 48 6.1 Conclusion .. 48 6.2 Future Work .. 49 參考文獻 .. 50 | |
dc.language.iso | en | |
dc.title | 搜尋結果多樣性問題中,基於二項分布子議題滿足度之研究 | zh_TW |
dc.title | A Study on Binomial-distribution-based Subtopic Satisfaction Model for Search Result Diversification Problem | en |
dc.type | Thesis | |
dc.date.schoolyear | 100-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 魏志達,邱志義 | |
dc.subject.keyword | 搜尋結果多樣性,子議題新穎度, | zh_TW |
dc.subject.keyword | Search Result Diversity,Subtopic Novelty, | en |
dc.relation.page | 52 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2012-08-14 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
顯示於系所單位: | 資訊工程學系 |
文件中的檔案:
檔案 | 大小 | 格式 | |
---|---|---|---|
ntu-101-1.pdf 目前未授權公開取用 | 2.35 MB | Adobe PDF |
系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。