本文選題：問答系統(tǒng)　切入點：本體　出處：《華東理工大學》2013年碩士論文

【摘要】：隨著互聯(lián)網技術的發(fā)展,信息量暴增,給人們的生活發(fā)生了翻天覆地的變化�，F(xiàn)在,人們已經習慣于在互聯(lián)網上獲取各種各樣的信息。這主要歸功與搜索引擎技術的發(fā)展。然而,傳統(tǒng)的搜索引擎仍然有一些缺陷。比如,用戶只能通過關鍵字詞進行檢索,這并不能充分表達用戶的搜索意圖；又比如,傳統(tǒng)索索引擎返回許多相關的候選結果,待用戶從中找到其目標結果,這樣的召回率往往很低,用戶體驗較差。針對以上問題,自動問答系統(tǒng)運用而生。用戶使用自然語言問句向自動問答系統(tǒng)提問,系統(tǒng)返回的是對問句最直接最簡單的答案。 本文首先對現(xiàn)在已有的問答系統(tǒng)中的技術理論進行了分析,闡述了各個模塊所使用技術的優(yōu)勢和不足。然后,參照國外一些本體構建工程,按照這些本體工程提出的構建方法論和經驗,構建了小型的零售領域本體知識庫,用于檢索面向受限領域的知識。以本體在問答系統(tǒng)中的應用為出發(fā)點,提出了基于零售領域本體庫的問答系統(tǒng)的答案抽取方法。用戶使用自然語言問句向系統(tǒng)提問,經過分詞、去停用詞、語義標注等步驟,使用淺層語義分析技術對問句進行分析,得到問句中的已知和未知信息,在此基礎上生成問句向量。最后使用SPARQL查詢語言從本體庫中查找問題答案。由于是直接查找問題的答案,有效地提高了系統(tǒng)的召回率,改善了用戶體驗�；谝陨侠碚�,設計并實現(xiàn)了面向零售領域的自動問答系統(tǒng)模型。通過應用驗證了本文提出的相關技術,證明了本系統(tǒng)相關理論的可行性。
[Abstract]:With the development of Internet technology, the amount of information increases dramatically.Nowadays, people are used to getting all kinds of information on the Internet.This is mainly due to the development of search engine technology.However, the traditional search engine still has some defects.For example, users can only search by keywords, which does not fully express the user's search intention. For example, the traditional Sosso engine returns many related candidate results, and the user finds the target result from the search engine.Such recall rates tend to be low and the user experience is poor.In view of the above questions, the automatic question answering system is used.Users use natural language questions to question the automatic question answering system, which returns the most direct and simple answer to the question sentence.In this paper, the technical theory of the question and answer system is analyzed, and the advantages and disadvantages of the technologies used in each module are expounded.Then, referring to some overseas ontology construction projects, according to the construction methodology and experience proposed by these ontology projects, a small retail domain ontology knowledge base is constructed, which is used to retrieve the restricted domain knowledge.Based on the application of ontology in Q & A system, an answer extraction method based on retail domain ontology library is proposed.Users use natural language questions to ask questions to the system, through word segmentation, deactivation words, semantic tagging and other steps, using shallow semantic analysis technology to analyze the question sentence, and get the known and unknown information in the question sentence.On this basis, the question vector is generated.Finally, the SPARQL query language is used to find the answers from the ontology library.It can improve the recall rate of the system and improve the user experience.Based on the above theory, an automatic question answering system model for retail field is designed and implemented.The feasibility of the related theory of the system is proved by the application of the related technology proposed in this paper.
【學位授予單位】：華東理工大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP391.3

【引證文獻】

相關碩士學位論文 前1條

1 李艷;基于本體的毒品案件信息抽取研究[D];西北大學;2013年

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本文編號：1703625