本文選題：答案總結(jié)　切入點：信息需求　出處：《哈爾濱工業(yè)大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：近年來，社區(qū)問答門戶網(wǎng)站作為新興的一種知識共享平臺給問答系統(tǒng)帶來了新的契機(jī)，為問答系統(tǒng)提供大量可用的問句及相應(yīng)的答案信息。因其具有的交互性和開放性的特點，使它能夠很好的滿足用戶的信息需求。大量的在線社區(qū)問答門戶應(yīng)運(yùn)而生，其中包括百度知道，搜搜問問，天涯問答等等。用戶獲取知識的這一新手段，說明了傳統(tǒng)搜索引擎僅僅基于關(guān)鍵詞的查詢方式已經(jīng)不能滿足用戶準(zhǔn)確快速搜索自己信息的需求。社區(qū)問答門戶允許用戶通過發(fā)帖的形式進(jìn)行提問，提問內(nèi)容中可以包括問題的內(nèi)容以及對問題上下文語境進(jìn)行補(bǔ)充的問題描述，所有用戶都可以對這個問題進(jìn)行回答，提問者也可以從答案中選擇一個作為最佳答案。 然而，由于用戶對自己想要獲取的信息領(lǐng)域并不熟悉，用戶可能無法很好的組織自己的查詢語言來幫助自己得到想要的信息需求。因此本課題將用戶查詢問句在社區(qū)問答門戶上進(jìn)行一個擴(kuò)展，同時擴(kuò)展的還有它們的問題描述信息和答案信息。將包含各種不同信息需求的問題集與答案集進(jìn)行協(xié)同聚類，獲得與用戶查詢問句相關(guān)的各個方面的信息需求。 在不同的問題描述（上下文信息）之下的同一問題，它們產(chǎn)生的答案極可能是完全不同的。例如對于問題“如何買手機(jī)？”，當(dāng)問題描述是“我應(yīng)該到哪里去買”和“怎樣才能買到便宜的”時，用戶想要得到的信息需求是迥異的。為了解決這個問題，在協(xié)同聚類模型中引入了以問題描述為基礎(chǔ)的約束條件。 同時，社區(qū)問答回答者所提供的答案質(zhì)量良莠不齊，有時在提供有用信息的同時可能附加了無用的信息甚至是錯誤的信息。這樣高冗余的信息，難以應(yīng)用于問答系統(tǒng)之中。本課題收集答案中的文本特征以及非文本特征，建立答案排序模型，通過協(xié)同聚類后的簇中排序好的信息來進(jìn)行答案總結(jié)。 大量的答案集中必然會包含有較多的重復(fù)信息，而這些回答可能存在表述上的區(qū)別而無法通過簡單的相似度計算來進(jìn)行檢測。這樣，本課題建立一種答案相似檢測模型，通過層次多分類器投票的方法，來檢測答案中存在的重復(fù)信息，并進(jìn)行去除，最終得到正確的答案總結(jié)。
[Abstract]:In recent years, as a new knowledge sharing platform, the community Q & A portal has brought a new opportunity to the Q & A system, providing a large number of questions and corresponding answer information for the Q & A system, because of its interactive and open characteristics. So that it can very well meet the information needs of users. A large number of online community Q & A portal emerged as the times require, including Baidu know, search and ask, Tianya question and answer and so on. It shows that the traditional search engine only based on keywords can no longer meet the needs of users to search their own information accurately and quickly. The community Q & A portal allows users to ask questions through posting. The content of the question can include the content of the question and the supplementary description of the context of the question. All users can answer the question, and the questioner can choose one of the answers as the best answer. However, because users are not familiar with the field of information they want to access, Users may not be able to organize their own query languages to help them get the information they want. At the same time, the problem description information and the answer information are extended. The question set and the answer set, which contain different information requirements, are cooperatively clustered to obtain the information requirements of various aspects related to the user query question. The same question under different question descriptions (contextual information), they are likely to produce completely different answers. For example, for the question "how to buy a phone?" When the problem description is "where should I buy" and "how can I buy cheap", the information users want is very different. To solve this problem, The constraints based on problem description are introduced into the cooperative clustering model. At the same time, the quality of the answers provided by community question-and-answer respondents is mixed, and sometimes useful information may be accompanied by useless information or even false information. It is difficult to be applied to the question answering system. This paper collects the text features and non-text features of the answers, establishes the sorting model of the answers, and summarizes the answers through the sorted information in the cluster after cooperative clustering. A large number of answer sets are bound to contain more repeated information, and these answers may differ in expression and cannot be detected by simple similarity calculation. Through the method of hierarchical multi-classifier voting, the repeated information in the answer is detected and removed, and finally the correct answer summary is obtained.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP391.1

【參考文獻(xiàn)】

相關(guān)期刊論文 前8條

1 夏天,樊孝忠,劉林,駱正華;基于ALICE的漢語自然語言接口[J];北京理工大學(xué)學(xué)報;2004年10期

2 秦兵,劉挺,王洋,鄭實福,李生;基于常問問題集的中文問答系統(tǒng)研究[J];哈爾濱工業(yè)大學(xué)學(xué)報;2003年10期

3 徐凱華;張德干;姚琳;;基于Agent的人機(jī)對話系統(tǒng)的設(shè)計與實現(xiàn)[J];計算機(jī)工程;2007年16期

4 夏天,樊孝忠,劉林;ALICE機(jī)理分析與應(yīng)用研究[J];計算機(jī)應(yīng)用;2003年09期

5 姚琳;梁春霞;張德干;;基于實例推理的人機(jī)對話系統(tǒng)的設(shè)計與實現(xiàn)[J];計算機(jī)應(yīng)用;2007年03期

6 方慧;;TREC發(fā)展歷程及現(xiàn)狀分析[J];新世紀(jì)圖書館;2010年01期

7 伍大勇;張宇;劉挺;;中文交互式問答用戶問題相關(guān)檢測研究[J];中文信息學(xué)報;2010年03期

8 李偉通;皮德常;;基于統(tǒng)計學(xué)習(xí)的自然語言對話系統(tǒng)的設(shè)計與實現(xiàn)[J];微計算機(jī)應(yīng)用;2008年07期

，

本文編號：1613863