本文關鍵詞： 信息檢索模型 概念圖 需求分析 相似度計算　出處：《上海交通大學》2013年碩士論文　論文類型：學位論文

【摘要】：信息檢索模型的研究和發(fā)展已經(jīng)歷經(jīng)70余載，在過去相當一段時間里，信息檢索還只限于專業(yè)人員使用，模型的實現(xiàn)原理也比較簡單，人們獲取信息的途徑并不依賴于信息檢索，因此用戶對于信息檢索的需求還不是十分迫切。隨著互聯(lián)網(wǎng)的興起，人們信息檢索的需求也逐漸擴大。在紛亂龐雜的信息海洋中，如何準確地獲取滿足需求的信息也成為信息檢索研究中一項刻不容緩的工作。當前大多搜索引擎在提供搜索服務的時候總有一些方面不如人意，究其原因，是因為它們把用戶的需求簡單地拆分成了若干個毫無關系的關鍵詞，而沒有把需求當作一個概念整體來看待，于是就丟失了關鍵詞之間存在的語義信息。 本文首先從概念圖的相關理論研究入手，強調(diào)了概念分析在表征用戶需求意圖上的重要性�；诟拍顖D的檢索模型，通過需求概念圖的標引來保持用戶需求的概念內(nèi)涵，在檢索時融入概念圖匹配和語義相似度計算的方法，從而提升檢索的準確率。本文客觀地分析了實現(xiàn)該檢索模型的重重困難，同時重新考量了各項相關技術，創(chuàng)新性地提出了需求概念圖導引下的檢索模型。 圍繞這個模型，本文先著重討論了需求概念圖標引的方法，分析用戶需求的相關特點，并結合詞匯知識獲取等方法，探討E-A-V形式的概念圖自動標引。其次，我們又詳細介紹了相關語義相似度計算以及概念圖相似度計算的方法，，對比了各自的優(yōu)劣。最后是檢索模型實現(xiàn)的各種細節(jié)，主要介紹了概念圖實際應用時的實踐經(jīng)驗，為今后概念圖完全應用于信息檢索，真正實現(xiàn)語義搜索提供一些有益的思路。
[Abstract]:The research and development of information retrieval model has gone through more than 70 years, in the past quite a period of time, information retrieval is only limited to the use of professionals, the implementation principle of the model is also relatively simple. People's access to information does not depend on information retrieval, so users' demand for information retrieval is not very urgent. With the rise of the Internet. People's demand for information retrieval is also gradually expanding. In the chaotic sea of information. How to accurately obtain the information to meet the needs has become an urgent task in the information retrieval research. At present, most search engines are always unsatisfactory in some aspects when providing search services, which is the reason. Because they simply split the user's requirements into several unrelated keywords and did not treat the requirements as a whole, they lost the semantic information that exists between keywords. This paper starts with the related theoretical research of concept map, and emphasizes the importance of concept analysis in representing the intention of user demand. The retrieval model based on concept graph is proposed in this paper. Through the indexing of the requirement concept map to keep the concept connotation of the user requirement, the method of concept map matching and semantic similarity calculation is incorporated in the retrieval. In order to improve the accuracy of retrieval, this paper objectively analyzes the difficulties of implementing the retrieval model, reconsiders the relevant technologies, and creatively puts forward the retrieval model guided by the requirement concept map. Around this model, this paper first discusses the method of conceptual icon citation of requirements, analyzes the relevant characteristics of user requirements, and combines the methods of acquisition of lexical knowledge. E-A-V form of concept map automatic indexing. Secondly, we also introduce the relevant semantic similarity calculation and concept map similarity calculation methods in detail. Finally, the details of the implementation of the retrieval model are discussed, and the practical experience in the practical application of the concept map is mainly introduced, so that the concept map can be fully applied to information retrieval in the future. The real implementation of semantic search provides some useful ideas.
【學位授予單位】：上海交通大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP391.3

【參考文獻】

相關期刊論文 前2條

1 劉挺;馬金山;;漢語自動句法分析的理論與方法[J];當代語言學;2009年02期

2 陸汝占,靳光瑾;現(xiàn)代漢語研究的新視角[J];語言文字應用;2004年02期

相關博士學位論文 前2條

1 劉磊;概念內(nèi)涵屬性計算研究[D];上海交通大學;2011年

2 朱海平;基于概念圖匹配的語義搜索[D];上海交通大學;2006年

本文編號：1461553