請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65817完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 鄭卜壬(Pu-Jen Cheng) | |
| dc.contributor.author | Weng Kit Lei | en |
| dc.contributor.author | 李永杰 | zh_TW |
| dc.date.accessioned | 2021-06-17T00:12:47Z | - |
| dc.date.available | 2017-07-01 | |
| dc.date.copyright | 2012-07-26 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-07-10 | |
| dc.identifier.citation | [1] Z. Bar-Yossef and N. Kraus. Context-Sensitive Query Auto-Completion. In WWW 2011.
[2] M. Barouni-Ebrahimi and A. Ghorbani. On Query Completion in Web Search Engines Based on Query Stream Mining. In WI 2007. [3] H. Bast and I. Weber. Type Less, Find More: Fast Autocompletion Search with a Succinct Index. In SIGIR 2006. [4] S. Bhatia, D. Majumdar and P. Mitra. A Novel Approach for Frequent Phrase Mining in Web Search Engine Query Streams. In SIGIR 2011. [5] S. Bhatia, D. Majumdar and P. Mitra. Query Suggestions in the Absence of Query Logs. In SIGIR 2011. [6] H. Cao, D. Jiang, J. Pei, E. Chen and H. Li. Towards Context-Aware Search by Learning A Very Large Variable Length Hidden Markov Model from Search Logs. In WWW 2009. [7] H. Cao, D. Jaing, J. Pei, Q. He, Z. Liao, E. Chen and H. Li. Context-Aware Query Suggestion by Mining Click-Through and Session Data. In KDD 2008. [8] H, Duan and B. Hsu. Online Spelling Correction for Query Completion. In WWW 2011. [9] R. Jones, B. Rey, O. Madani and W. Greiner. Generating Query Substitutions. In WWW 2006. [10] Z. Liao, D. Jiang, E. Chen, J. Pei, H. Cao and H. Li. Query Suggestions Using Query-Flow Graphs. In ACM Transactions on Intelligent Systems and Technology 2011. [11] Q. Mei, D. Zhou and K. Church. Query Suggestion Using Hitting Time. In CIKM 2008. [12] E. Sadikov, J. Madhavan , L. Wang and A. Halevy. Clustering query refinements by user intent. In WWW 2011. [13] Y. Song and L, He. Optimal Rare Query Suggestion with Implicit User Feedback. In WWW 2010. [14] X. Wang and C. Zhai. Mining Term Association Patterns from Search Logs for Effective Query Reformulation. In CIKM 2008 [15] http://en.wikipedia.org/wiki/Yahoo!_Personals | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65817 | - |
| dc.description.abstract | 關鍵字的自動完成是各個搜尋領域的重要應用之一。它在檔案搜尋、網路搜尋，甚致是整合型程式碼編輯器，都有著重要的應用。它可以預測使用者的關鍵字並省下使用者的鍵盤輸入。
由於網路的急速成長以及移動裝置的成熟，在移動裝置上進行網絡搜尋是件很重要的事。亦因為手機等移動置的輸入介面很有限，沒有像個人電腦的硬體鍵盤，所以在網路搜尋上提供關鍵字的自動完成就變得更重要了。 在這本篇論文中，我們會建立一個以情境概念和脈絡為基礎的模型去改進關鍵字的自動完成。它會使用非監督式分群法去找出搜尋引擎記錄檔中關鍵字的不同概念，以及衡量關鍵字之間的聯繫性。然後根據使用者最近使用過的關鍵字，配合概念的變動而推薦最可能的詞組作為自動完成。這個模型還可以利用替代性法則，用來產生過往沒有在搜尋引擎中出現的詞組，以減輕搜尋在建立模型時的資料不足。在實驗部份，我們會以真正的搜尋記錄檔作為檢測，以此表現模型的可行性。我們還比較過去的自動完成的方法，結果顯示我們的方法有著明顯的改進。 | zh_TW |
| dc.description.abstract | Query completion is an application in many search domains, such as file search, programming editor word suggestions or the web search. It is used to save the user keystroke in every domain. As the rapid growth of the web and the increasing popular of mobile devices, searching web data from mobile device is an important issue. Therefore, query completion in web search is becoming more and more important because it can save users’ effort from the hard inputting mobile device. In this paper, we construct a concept and context base model to help to improve the query completion. It uses a clustering method to construct the concept of query and measure the dependences of queries in search log. This model also can generate the unseen query from log by the replaceable criteria to alleviate the sparseness problem. We experiment the model in real query log data to demonstrate the feasibility. We compare it with context base method proposed in the past. It also gets a significant improvement. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T00:12:47Z (GMT). No. of bitstreams: 1 ntu-101-R99922048-1.pdf: 3071985 bytes, checksum: ee08ef2a3b0f438f84f03d4a9468a834 (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
誌謝 ii 摘要 iii Abstract iv List of figure vii List of table viii 1. Introduction 1 2. Related Work 4 3. Methodology 8 3.1 Concept Creation and Concept Transition 8 3.1.1 Offline Clustering 9 3.1.2 Concept Transition Probability 10 3.2 Concept Completion 11 3.2.1 Concept Selection 11 3.2.2 Word Completion 13 3.2.3 Query Completion 14 3.3 Entropy Merge 16 4. Experiment 19 4.1 Experiment Setting 19 4.1.1 Click log, Session Data, Query Pair Cleaning 19 4.2 Query Pairs Experiment 21 4.2.1 Query Pairs Experiment – All Pairs 24 4.2.2 Query Pairs Experiment – Dependent Pairs 31 4.3 Suggestion Example 32 4.4 Keystroke Experiment 34 4.4.1 Simulate Process 35 5. User Study 37 5.1 User Study Environment 37 5.2 User Study Result 38 6. Conclusion and Future Work 40 7. REFERENCES 42 | |
| dc.language.iso | en | |
| dc.subject | 情境脈絡 | zh_TW |
| dc.subject | 關鍵字的自動完成 | zh_TW |
| dc.subject | 搜尋關鍵字的擴展與建議 | zh_TW |
| dc.subject | 關鍵字的熵 | zh_TW |
| dc.subject | 搜尋引擎記錄檔 | zh_TW |
| dc.subject | query entropy | en |
| dc.subject | query expansion | en |
| dc.subject | query suggestion | en |
| dc.subject | context aware | en |
| dc.subject | query log | en |
| dc.subject | Query auto completion | en |
| dc.title | 利用情境脈絡協助關鍵字查詢的自動完成 | zh_TW |
| dc.title | Automatic Concept and Context Based Query Completion | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳信希(HSIN-HSI CHEN),盧文祥(Wen-Hsiang Lu),蔡銘峰(Ming-Feng Tsai) | |
| dc.subject.keyword | 關鍵字的自動完成,搜尋關鍵字的擴展與建議,情境脈絡,搜尋引擎記錄檔,關鍵字的熵, | zh_TW |
| dc.subject.keyword | Query auto completion,query expansion,query suggestion,context aware,query log,query entropy, | en |
| dc.relation.page | 42 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2012-07-11 | |
| 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 | |
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| ntu-101-1.pdf 未授權公開取用 | 3 MB | Adobe PDF |
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