Naive Evaluation of Recursively Defined Relations

Bancilhon, François

doi:10.1007/978-1-4612-4980-1_17

Cited by 119 publications

(50 citation statements)

References 3 publications

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“…The simplest of these is the semi-naïve algorithm [7], which runs in O(N 4 ) time, and essentially prescribes repeated application of the belief update equation. If running as a peer-to-peer system, the semi-naïve algorithm may be easily parallelized, requiring O(N 3 ) computations per node [2].…”

Section: Computationmentioning

confidence: 99%

Trust Management for the Semantic Web

Richardson

Agrawal

Domingos

2003

Lecture Notes in Computer Science

696

385

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Abstract. Though research on the Semantic Web has progressed at a steady pace, its promise has yet to be realized. One major difficulty is that, by its very nature, the Semantic Web is a large, uncensored system to which anyone may contribute. This raises the question of how much credence to give each source. We cannot expect each user to know the trustworthiness of each source, nor would we want to assign top-down or global credibility values due to the subjective nature of trust. We tackle this problem by employing a web of trust, in which each user maintains trusts in a small number of other users. We then compose these trusts into trust values for all other users. The result of our computation is not an agglomerate "trustworthiness" of each user. Instead, each user receives a personalized set of trusts, which may vary widely from person to person. We define properties for combination functions which merge such trusts, and define a class of functions for which merging may be done locally while maintaining these properties. We give examples of specific functions and apply them to data from Epinions and our BibServ bibliography server. Experiments confirm that the methods are robust to noise, and do not put unreasonable expectations on users. We hope that these methods will help move the Semantic Web closer to fulfilling its promise.

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Section: Computationmentioning

confidence: 99%

Trust Management for the Semantic Web

Richardson

Agrawal

Domingos

2003

Lecture Notes in Computer Science

696

385

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“…However, it also raises the complexity of query evaluation. The problem of efficiently computing Datalog queries has attracted a great deal of attention in the database and logic programming communities e.g., [6,8,12,14,17,18,24,25,27].…”

Section: Introductionmentioning

confidence: 99%

Nonrecursive incremental evaluation of Datalog queries

Dong

Topor

1995

Ann Math Artif Intell

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We consider the problem of repeatedly evaluating the same (computationally expensive) query to a database that is being updated between successive query requests. In this situation, it should be possible to use the difference between successive database states and the answer to the query in one state to reduce the cost of evaluating the query in the next state. We use nonrecursive Datalog (which are unions of conjunctive queries) to compute the differences, and call this process "incremental query evaluation using conjunctive queries."After formalizing the notion of incremental query evaluation using conjunctive queries, we give an algorithm that constructs, for each regular chain query (including transitive closure as a special case), a nonrecursive Datalog program to compute the difference between the answer after an update and the answer before the update. We then extend this result to weakly regular queries, which are regular chain programs augmented with conjunctive queries having the so-called cartesian-closed increment property, and to the case of unbounded-set insertions where the sets are binary cartesian products. Finally, we show that the class of conjunctive queries with the cartesian-closed increment property is decidable.

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“…Trên thực tế, đã có rất nhiều thuật toán được thiết kế để tính bao đóng bắc cầu của một quan hệ trong cơ sở dữ liệu truyền thống như Naive [24], Semi-naive [1][2][3], Smart [27,28], Minimal evaluations [28], Warshall [30] và Warren [31]. Chúng được phân loại thành hai nhóm chính, các thuật toán lặp (Naive, Semi-naive, Smart, Minimal evaluations) và các thuật toán tính trực tiếp (Warshall và Warren).…”

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