本文選題：數(shù)據(jù)庫可用性 + Causality與Responsibility問題��； 參考：《浙江大學(xué)》2017年博士論文

【摘要】：偏好查詢(如反Top-k查詢、反Skyline查詢等)是數(shù)據(jù)庫領(lǐng)域重要的查詢類型之一,它能夠根據(jù)用戶指定的偏好要求進行個性化查詢,并向用戶返回與其偏好相匹配的查詢結(jié)果。偏好查詢在多標(biāo)準(zhǔn)決策支持和個性化推薦等方面具有廣闊的應(yīng)用前景。當(dāng)前的數(shù)據(jù)庫查詢(包括偏好查詢)僅僅向用戶返回查詢結(jié)果。如果查詢結(jié)果不是用戶想要的,現(xiàn)有的數(shù)據(jù)庫系統(tǒng)既不能向用戶解釋為什么會得到這樣的結(jié)果,也無法給出有效的建議來幫助用戶得到滿意的查詢結(jié)果。查詢結(jié)果可用性研究正是針對當(dāng)前數(shù)據(jù)庫系統(tǒng)的這一不足而展開,其目標(biāo)旨在向用戶解釋為什么會產(chǎn)生當(dāng)前的查詢結(jié)果,并幫助用戶得到使其滿意的查詢結(jié)果,從而使用戶能夠更加高效、方便地使用數(shù)據(jù)庫,提高用戶對數(shù)據(jù)庫的滿意度。然而查詢結(jié)果可用性研究依賴于具體的查詢。不同的查詢所對應(yīng)的查詢結(jié)果可用性問題解決方案也不相同。但當(dāng)前的查詢結(jié)果可用性研究大多關(guān)注關(guān)系型數(shù)據(jù)庫查詢。因此,現(xiàn)有的查詢結(jié)果可用性技術(shù)不能有效地解決偏好查詢上的查詢結(jié)果可用性問題。鑒于此,本文以反Top-k查詢和反Skyline查詢?yōu)槔?對偏好查詢的查詢結(jié)果可用性進行了深入地研究,研究內(nèi)容主要包括:(1)反Top-k查詢和反Skyline查詢上的Causality與Responsibility問題處理。當(dāng)查詢結(jié)果中包含了用戶不想要的對象,或者用戶想要的對象沒有包含在查詢結(jié)果中,那么用戶可能想要知道導(dǎo)致這些查詢結(jié)果的原因及其相應(yīng)的責(zé)任大小,以便更好地理解原有的查詢。為此,本文將開展反Top-k查詢和反Skyline查詢上的Causality與Responsibility問題處理研究,以幫助用戶找出導(dǎo)致其不想要的結(jié)果出現(xiàn)或想要的結(jié)果沒有出現(xiàn)的原因(即Causality),并計算每個原因的責(zé)任大小(即 Responsibility)。(2)反Top-k查詢上的 Why-not 與 Why 問題處理。Causality 與 Responsibility問題處理只向用戶解釋當(dāng)前查詢結(jié)果產(chǎn)生的原因,而不能幫助用戶得到其想要的查詢結(jié)果。因此,本文將開展反Top-k查詢上的Why-not與Why問題處理研究。其中,Why-not問題是將用戶想要但卻沒有出現(xiàn)在查詢結(jié)果中的對象包含在查詢結(jié)果中;Why問題旨在將用戶不想要但卻出現(xiàn)在查詢結(jié)果中的對象從查詢結(jié)果中排除。(3)反Top-k查詢和反Skyline查詢上的Why-few與Why-many問題處理。在實際應(yīng)用中,查詢可能返回太多或者太少(甚至為空)的答案對象。若答案對象太多,用戶往往無從選擇,而答案對象太少,用戶又會沒有選擇的余地。這兩種情況都不是用戶想要的。所以,針對答案對象太多或太少(甚至為空)的情況,本文研究了反Top-k查詢和反Skyline查詢上的Why-few與Why-many問題。其中,Why-few問題針對的是原查詢結(jié)果中答案對象太少甚至為空的情況,以幫助用戶增加答案對象;Why-many問題針對的是原查詢結(jié)果中答案對象太多的情況,以幫助用戶減少答案對象。(4)反Top-k查詢結(jié)果可用性分析系統(tǒng)。集成上述研究成果,本文開發(fā)了一個反Top-k查詢結(jié)果可用性分析系統(tǒng)。該系統(tǒng)能夠根據(jù)用戶的反饋信息向其解釋為什么會產(chǎn)生當(dāng)前的查詢結(jié)果,并向用戶給出相應(yīng)的建議使其能夠得到滿意的查詢結(jié)果。
[Abstract]:Preference queries (such as anti Top-k query, anti Skyline query, etc.) are one of the most important query types in the database domain. It can make personalized queries according to the user's specified preference and return the query results that match their preferences to the user. Preference query has a wide application in multi standard decision support and personalized recommendation. The current database query (including a preference query) returns only the result of the query to the user. If the query result is not what the user wants, the existing database system can neither explain to the user why it will get such a result nor give effective suggestions to help the user get satisfactory results. The result of the query can be obtained. The purpose of usability research is to address the shortcoming of the current database system, which aims to explain to the user why the current query results are generated and to help the user get the satisfactory results, so that the user can use the database more efficiently, conveniently, and improve the user's satisfaction with the database. Results availability studies are dependent on specific queries. The availability problem solutions of query results for different queries are also different. However, most current query results availability studies focus on relational database queries. Therefore, existing query results availability can not effectively solve query results on preference queries. In view of this, this article takes the anti Top-k query and anti Skyline query as an example to make a thorough study of the availability of query results for preference queries. The main contents include: (1) Causality and Responsibility problems on anti Top-k queries and anti Skyline queries. The object that the user wants is not included in the query result, so the user may want to know the reason for the result of the query and the size of the responsibility to better understand the original query. For this purpose, this article will carry out the research on the Causality and Responsibility problems on the anti Top-k query and the anti Skyline query to help The user finds out the cause of the result that the unwanted result appears or wanted (that is, Causality), and calculates the size of the responsibility for each cause (Responsibility). (2) the Why-not and Why problems on the anti Top-k query process the.Causality and Responsibility problems to explain the current query results to the user only. It does not help users get their desired results. Therefore, this article will conduct research on Why-not and Why problems on anti Top-k queries. In this, the Why-not problem is that the object that the user wants but not in the query result is included in the query result; the Why problem aims to make the user unwanted but appear in the query result. The objects in the query are excluded from the query results. (3) the Why-few and Why-many problems on the anti Top-k query and the anti Skyline query. In practical applications, the query may return to too many or too few (even empty) answers. If the answer object is too many, the user often has no choice but the answer is too few and the user will have no choice. These two cases are not what the user wants. So, for the case of too many or too little (or even empty) answers, this paper studies the Why-few and Why-many problems on the anti Top-k query and the anti Skyline query. In this case, the Why-few problem is aimed at the case that the answer object is too few or even empty in the original query to help the user to increase the answer. Case object; the Why-many problem is aimed at the fact that there are too many answers in the original query result to help the user to reduce the answer object. (4) the anti Top-k query result availability analysis system. Integrated the above research results, this paper develops an anti Top-k query result availability analysis system. The system can be based on the feedback information of the user to it Explains why the current query results are generated, and gives corresponding suggestions to users so that they can get satisfactory query results.

【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：TP311.13

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