Recently, a graph labeling technique based on prime numbers has been suggested for reducing the costly transitive closure computations in RDF query languages. The suggested prime number graph labeling provides the benefit of fast query processing by a simple divisibility test of labels. However, it has an inherent problem that originates with the nature of prime numbers. Since each prime number must be used exclusively, labels can become significantly large. Therefore, in this paper, we introduce a novel optimization technique to effectively reduce the problem of label overflow. The suggested idea is based on graph decomposition. When label overflow occurs, the full graph is divided into several sub-graphs, and nodes in each sub-graph are separately labeled. Through experiments, we also analyze the effectiveness of the graph decomposition optimization, which is evaluated by the number of divisions.

An expectation for more intelligent Web is recently being reflected through the new research field called Semantic Web. In this paper, related with Semantic Web security, we introduce an RDF triple based access control model having explicit authorization propagation by inheritance and implicit authorization propagation by inference. Especially, we explain an authorization conflict problem between the explicit and the implicit authorization propagation, which is an important concept in access control for Semantic Web. We also propose a novel conflict detection algorithm using graph labeling techniques in order to efficiently find authorization conflicts. Some experimental results show that the proposed detection algorithm has much better performance than the existing detection algorithm when data size and number of specified authorizations become larger.

Web service users are overwhelmed by the amount of information presented to them and have difficulties in finding the information that they need. Therefore, a recommendation system that predicts users' taste is an essential factor for the success of businesses. However, recommendation systems require users' personal information and can thus lead to serious privacy violations. To solve this problem, many research has been conducted about protecting personal information in recommendation systems and implementing differential privacy, a privacy protection technique that inserts noise into the original data. However, previous studies did not examine the following factors in applying differential privacy to recommendation systems. First, they did not consider the sparsity of user rating information. The total number of items is much more than the number of user-rated items. Therefore, a rating matrix created for users and items will be very sparse. This characteristic renders the identification of user patterns in rating matrixes difficult. Therefore, the sparsity issue should be considered in the application of differential privacy to recommendation systems. Second, previous studies focused on protecting user rating information but did not aim to protect the lists of user-rated items. Recommendation systems should protect these item lists because they also disclose user preferences. In this study, we propose a differentially private recommendation scheme that bases on a grouping method to solve the sparsity issue and to protect user-rated item lists and user rating information. The proposed technique shows better performance and privacy protection on actual movie rating data in comparison with an existing technique.

Access control involves a check to see if a user has an access right to a resource and then a decision is made as to whether his/her access to the resource is to be allowed or denied. Typical access control models are the Discretionary Access Control Model, the Mandatory Access Control Model, and the Role-Based Access Control Model. Today, the Role-Based Access Control Model has become popular and is recognized as an effective method. However, until now, the Role-Based Access Control Model was adequate only for bureaucracy organizations, in which some roles are standardized and organizational hierarchy is stable. Team-Based Access Control models that were designed for team-based organizations have been proposed, but they do not reflect some features of an adhocracy organization, which are organic, temporary, not standardized, changeable, and obscure in terms of hierarchical relationship, such as a Task Force Team in the company. This study shows the characteristics of an adhocracy organization that differ from the existing bureaucracy organization, and then shows why existing access control models have caused some problems. Finally, a revised Role-Based Access Control model is proposed to solve those problems and is analyzed according to main evaluation standards.

Recently, for more efficient filtering of XML data, YFilter system has been suggested to exploit the prefix commonalities that exist among path expressions. Sharing the prefix commonality gives the benefit of improving filtering performance through the tremendous reduction in filtering machine size. However, exploiting the postfix commonality can also be useful for an XML filtering situation. For example, when a stream of XML messages does not have any defined schema, or users cannot remember the defined schema exactly, users often use the partial matching path queries which begins with the descendant axis ("//"), e.g., '//science/article/title', '//entertainment/article/title', and '//title'. If so, the registered XPath queries are most likely to have the postfix commonality, e.g., the sample queries share the partial path expressions 'article/title' and 'title'. Therefore, in this paper, we introduce a bottom-up filtering approach exploiting the postfix commonality against the top-down approach of YFilter exploiting the prefix commonality. Some experimental results show that our method has better filtering performance when registered XPath queries mainly consist of the partial matching path queries with the postfix commonality.

The Krivine-style evaluation mechanism is well-known in the implementation of higher-order functions, allowing to avoid some useless closure building. There have been a few type systems that can verify the safety of the mechanism. The incorporation of the proposed ideas into an existing compiler, however, would require significant changes in the type system of the compiler due to the use of some dedicated form of types and typing rules in the proposals. This limitation motivates us to propose an alternative light-weight Krivine typing mechanism that does not need to extend any existing type system significantly. This paper shows how GADTs (Generalized algebraic data types) can be used for typing a ZINC machine following the Krivine-style evaluation mechanism. This idea is new as far as we know. Some existing typed compilers like GHC (Glasgow Haskell compiler) already support GADTs; they can benefit from the Krivine-style evaluation mechanism in the operational semantics with no particular extension in their type systems for the safety. We show the GHC type checker allows to prove mechanically that ZINC instructions are well-typed, which highlights the effectiveness of GADTs.