52830913
Interaction between path and type constraints
Path constraints are capable of expressing inclusion and inverse relationships and have proved useful in modeling and querying semistructured data [Abiteboul and Vianu 1999; Buneman et al. 2000]. Types also constrain the structure of data and are commonly found in traditional databases. There has also been work on imposing structure or a type system on semistructured data for storing and querying semistructured data in a traditional database system [Alon et al. 2001; Deutsch et al. 1999a; Florescu and Kossmann 1999; Shanmugasundaram et al. 1999]. One wants to know whether complexity results for reasoning about path constraints established in the untyped (semistructured) context could carry over to traditional databases, and vice versa. It is therefore appropriate to understand the interaction between types and path constraints. In addition, XML [Bray et al. 1998], which may involve both an optional schema (e.g., DTDs or XML Schema [Thompson et al. 2001]) and integrity constraints, highlights the importance of the study of the interaction.This article investigates that interaction. In particular it studies constraint implication problems, which are important both in understanding the semantics of type/constraint systems and in query optimization. It shows that path constraints interact with types in a highly intricate way. For that purpose a number of results on path constraint implication are established in the presence and absence of type systems. These results demonstrate that adding a type system may in some cases simplify reasoning about path constraints and in other cases make it harder. For example, it is shown that there is a path constraint implication problem that is decidable in PTIME in the untyped context, but that becomes undecidable when a type system is added. On the other hand, there is an implication problem that is undecidable in the untyped context, but becomes not only decidable in cubic time but also finitely axiomatizable when a type system is imposed.
10950599
XPath satisfiability in the presence of DTDs
We study the satisfiability problem associated with XPath in the presence of DTDs. This is the problem of determining, given a query p in an XPath fragment and a DTD D, whether or not there exists an XML document T such that T conforms to D and the answer of p on T is nonempty. We consider a variety of XPath fragments widely used in practice, and investigate the impact of different XPath operators on satisfiability analysis. We first study the problem for negation-free XPath fragments with and without upward axes, recursion and data-value joins, identifying which factors lead to tractability and which to NP-completeness. We then turn to fragments with negation but without data values, establishing lower and upper bounds in the absence and in the presence of upward modalities and recursion. We show that with negation the complexity ranges from PSPACE to EXPTIME. Moreover, when both data values and negation are in place, we find that the complexity ranges from NEXPTIME to undecidable. Finally, we give a finer analysis of the problem for particular classes of DTDs, exploring the impact of various DTD constructs, identifying tractable cases, as well as providing the complexity in the query size alone.
38519945
Propagating XML constraints to relations
We present a technique for refining the design of relational storage for XML data based on XML key propagation. Three algorithms are presented: one checks whether a given functional dependency is propagated from XML keys via a predefined view; the others compute a minimum cover for all functional dependencies on a universal relation given XML keys. Experimental results show that these algorithms are efficient in practice. We also investigate the complexity of propagating other XML constraints to relations, and the effect of increasing the power of the transformation language. Computing XML key propagation is a first step toward establishing a connection between XML data and its relational representation at the semantic level.
5120213
Interaction between path and type constraints
XML [7], which is emerging as an important standard for data exchange on the World Wide Web, highlights the importance of the semistructured data. Although the XML standard itself does not require any schema or type system, a number of proposals [6, 15, 18] have been developed that roughly correspond to data definition languages. These allow one to constrain the structure of XML data by imposing a schema on it. These and other proposals also advocate the need for integrity constraints, another form of constraints that should, for example, be capable of expressing inclusion constraints and inverse relationships. The latter have recently been studied as path constraints in the context of semistructured data [4, 11]. It is likely that future XML proposals will involve both forms of constraint, and it is therefore appropriate to understand the interaction between them. This paper investigates that interaction. In particular it studies constraint implication problems, which are important both in understanding the semantics of type/constraint systems and in query optimization. A number of results on path constraint implication are established in the presences and absences of type systems. These results demonstrate that adding a type systems may in some cases simplify reasoning about path constraints and in other cases make it harder. For example, it is shown that there is a path constraint implication problem that is decidable in PTIME in the untyped context, but that becomes undecidable when a type system is added. On the other hand, there is an implication problem that is undecidable in the untyped context, but becomes not only decidable in cubic time but also finitely axiomatizable when a type system is imposed. Comments University of Pennsylvania Department of Computer and Information Science Technical Report No. MSCIS-98-16. This technical report is available at ScholarlyCommons: http://repository.upenn.edu/cis_reports/106
8618813
Reasoning about Keys for XML
We study absolute and relative keys for XML, and investigate their associated decision problems. We argue that these keys are important to many forms of hierarchically structured data including XML documents. In contrast to other proposals of keys for XML, these keys can be reasoned about efficiently. We show that the (finite) satisfiability problem for these keys is trivial, and their (finite) implication problem is finitely axiomatizable and decidable in PTIME in the size of keys.
53305032
Reasoning about keys for XML
We study absolute and relative keys for XML, and investigate their associated decision problems. We argue that these keys are important to many forms of hierarchically structured data including XML documents. In contrast to other proposals of keys for XML, we show that these keys are always (finitely) satisfiable, and their (finite) implication problem is finitely axiomatizable. Furthermore, we provide a polynomial time algorithm for determining (finite) implication in the size of keys. Our results also demonstrate, among other things, that the analysis of XML keys is far more intricate than its relational counterpart.
9423660
Learning to advertise
Content-targeted advertising, the task of automatically associating ads to a Web page, constitutes a key Web monetization strategy nowadays. Further, it introduces new challenging technical problems and raises interesting questions. For instance, how to design ranking functions able to satisfy conflicting goals such as selecting advertisements (ads) that are relevant to the users and suitable and profitable to the publishers and advertisers? In this paper we propose a new framework for associating ads with web pages based on Genetic Programming (GP). Our GP method aims at learning functions that select the most appropriate ads, given the contents of a Web page. These ranking functions are designed to optimize overall precision and minimize the number of misplacements. By using a real ad collection and web pages from a newspaper, we obtained a gain over a state-of-the-art baseline method of 61.7% in average precision. Further, by evolving individuals to provide good ranking estimations, GP was able to discover ranking functions that are very effective in placing ads in web pages while avoiding irrelevant ones.
3045710
Determining Success for Different Website Goals
In building a successful website it is imperative that the design matches the organization’s objectives, which should be well defined. Clearly, different types of websites will have different goals. Thus, determining success across websites is both goal and context specific. One measure of website success is satisfaction, and the resulting intent to return to a website. Built on theories from the IS success and information technology adoption literatures, this study investigated four variables believed to impact website satisfaction: information quality, system quality, perceived effectiveness, and social influence. Data was collected by surveying regular users of two different websites, each from a different category within a taxonomy of websites. Structural equation modeling techniques were used to test the proposed model of website success for each studied site. The results indicate that the determinants of satisfaction and overall successfulness of websites are both context dependent and goal specific.
1876424
A Similarity Reinforcement Algorithm for Heterogeneous Web Pages
Many machine learning and data mining algorithms crucially rely on the similarity metrics. However, most early research works such as Vector Space Model or Latent Semantic Index only used single relationship to measure the similarity of data objects. In this paper, we first use an Intra- and Inter- Type Relationship Matrix (IITRM) to represent a set of heterogeneous data objects and their inter-relationships. Then, we propose a novel similarity-calculating algorithm over the Inter- and Intra- Type Relationship Matrix. It tries to integrate information from heterogeneous sources to serve their purposes by iteratively computing. This algorithm can help detect latent relationships among heterogeneous data objects. Our new algorithm is based on the intuition that the intra-relationship should affect the inter-relationship, and vice versa. Experimental results on the MSN logs dataset show that our algorithm outperforms the traditional Cosine similarity.
16272457
SimFusion: measuring similarity using unified relationship matrix
In this paper we use a Unified Relationship Matrix (URM) to represent a set of heterogeneous data objects (e.g., web pages, queries) and their interrelationships (e.g., hyperlinks, user click-through sequences). We claim that iterative computations over the URM can help overcome the data sparseness problem and detect latent relationships among heterogeneous data objects, thus, can improve the quality of information applications that require com- bination of information from heterogeneous sources. To support our claim, we present a unified similarity-calculating algorithm, SimFusion. By iteratively computing over the URM, SimFusion can effectively integrate relationships from heterogeneous sources when measuring the similarity of two data objects. Experiments based on a web search engine query log and a web page collection demonstrate that SimFusion can improve similarity measurement of web objects over both traditional content based algorithms and the cutting edge SimRank algorithm.
5459818
Putting context into schema matching
Attribute-level schema matching has proven to be an important first step in developing mappings for data exchange, integration, restructuring and schema evolution. In this paper we investigate contextual schema matching, in which selection conditions are associated with matches by the schema matching process in order to improve overall match quality. We define a general space of matching techniques, and within this framework we identify a variety of novel, concrete algorithms for contextual schema matching. Furthermore, we show how common schema mapping techniques can be generalized to take more effective advantage of contextual matches, enabling automatic construction of mappings across certain forms of schema heterogeneity. An experimental study examines a wide variety of quality and performance issues. In addition, it demonstrates that contextual schema matching is an effective and practical technique to further automate the definition of complex data transformations.