31080635
An integrated two-stage model for intelligent information routing
A recent surge of subscriptions to online news services exemplifies the fact that people and organizations constantly need up-to-date information to stay competitive and make better informed decisions. However, many of these news services often require users to either manually input their profiles or subscribe to existing news channels. This results in lack of intelligence and personalization, and thus make these services less attractive to users. In this paper, an integrated model that combines query expansion with ranking function adaptation for online information routing is proposed and tested using two different large scale corpora. The experimental results show that this new model can deliver much better quality information than existing models.
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.
15362027
ETANA-DL: managing complex information applications - an archaeology digital library
Summary form only given. Archaeological research results in the generation of large quantities of heterogeneous information managed by different projects using custom information systems. We demonstrate a prototype digital library (DL) for integrating and managing archaeological data and providing services useful to various user communities. ETANA-DL is a model-based, componentized, extensible, archaeological DL that manages complex information sources using the client-server paradigm of the open archives initiative protocol for metadata harvesting (OAI-PMH). We present a prototype of ETANA-DL that builds on the 5S meta-model for developing for archaeological systems. We demonstrate our approach, used to integrate and handle highly heterogeneous data and the various services that ETANA-DL currently supports - searching, browsing, personal collections, workflows, discussions, annotations, etc. We are working on the structural aspects of the meta-model, and have used the results to develop advanced cross-collection searching and browsing services.
14252554
Discovering and Reconciling Semantic Conflicts: A Data Mining Perspective
Current approaches to semantic interoperability require human intervention in detecting potential conflicts and in defining how those conflicts may be resolved. This is a major impedance to achieving “logical connectivity”, especially when the dumber of disparate sources is large. In this paper, we demonstrate that the detection and reconciliation of semantic conflicts can be automated using tools and techniques developed by the data mining community. We describe a process for discovering such rules that represent the relationships among semanticaly related attributes and illustrate the effectiveness of our approach with examples.
4216648
Optimizing web search using web click-through data
The performance of web search engines may often deteriorate due to the diversity and noisy information contained within web pages. User click-through data can be used to introduce more accurate description (metadata) for web pages, and to improve the search performance. However, noise and incompleteness, sparseness, and the volatility of web pages and queries are three major challenges for research work on user click-through log mining. In this paper, we propose a novel iterative reinforced algorithm to utilize the user click-through data to improve search performance. The algorithm fully explores the interrelations between queries and web pages, and effectively finds "virtual queries" for web pages and overcomes the challenges discussed above. Experiment results on a large set of MSN click-through log data show a significant improvement on search performance over the naive query log mining algorithm as well as the baseline search engine.
15496678
Discovery of context-specific ranking functions for effective information retrieval using genetic programming
The Internet and corporate intranets have brought a lot of information. People usually resort to search engines to find required information. However, these systems tend to use only one fixed ranking strategy regardless of the contexts. This poses serious performance problems when characteristics of different users, queries, and text collections are taken into account. We argue that the ranking strategy should be context specific and we propose a , new systematic method that can automatically generate ranking strategies for different contexts based on genetic programming (GP). The new method was tested on TREC data and the results are very promising.
52151587
On XML integrity constraints in the presence of DTDs
The article investigates XML document specifications with DTDs and integrity constraints, such as keys and foreign keys. We study the consistency problem of checking whether a given specification is meaningful: that is, whether there exists an XML document that both conforms to the DTD and satisfies the constraints. We show that DTDs interact with constraints in a highly intricate way and as a result, the consistency problem in general is undecidable. When it comes to unary keys and foreign keys, the consistency problem is shown to be NP-complete. This is done by coding DTDs and integrity constraints with linear constraints on the integers. We consider the variations of the problem (by both restricting and enlarging the class of constraints), and identify a number of tractable cases, as well as a number of additional NP-complete ones. By incorporating negations of constraints, we establish complexity bounds on the implication problem, which is shown to be coNP-complete for unary keys and foreign keys.
1927184
Local manifold matching for face recognition
In this paper, we propose a novel classification method, called local manifold matching (LMM), for face recognition. LMM has great representational capacity of available prototypes and is based on the local linearity assumption that each data point and its k nearest neighbors from the same class lie on a linear manifold locally embedded in the image space. We present a supervised local manifold learning algorithm for learning all locally linear manifold structures. Then we propose the nearest manifold criterion for the classification in which the query feature point is assigned to the most matching face manifold. Experimental results show that kernel PCA incorporated with the LMM classifier achieves the best face recognition performance.
6232084
Query Optimization for Semistructured Data Using Path Constraints in a Deterministic Data Model
Path constraints have been studied for semistructured data modeled as a rooted edge-labeled directed graph [4, 11-13]. In this model, the implication problems associated with many natural path constraints are undecidable [11, 13]. A variant of the graph model, called the deterministic data model, was recently proposed in [10]. In this model, data is represented as a graph with deterministic edge relations, i.e., the edges emanating from any node in the graph have distinct labels. This model is more appropriate for representing, e.g., ACeDB [27] databases and Web sites. This paper investigates path constraints for the deterministic data model. It demonstrates the application of path constraints to, among others, query optimization. Three classes of path constraints are considered: the language Pc introduced in [11], an extension of Pc, denoted by Pcw, by including wildcards in path expressions, and a generalization of Pcw, denoted by P*c, by representing paths as regular expressions. The implication problems for these constraint languages are studied in the context of the deterministic data model. It is shown that in contrast to the undecidability result of [11], the implication and finite implication problems for Pc are decidable in cubic-time and are finitely axiomatizable. Moreover, the implication problems are decidable for Pcw. However, the implication problems for P*c are undecidable.
12168122
Structural properties of XPath fragments
We study structural properties of each of the main sublanguages of navigational XPath (W3c Recommendation) commonly used in practice. First, we characterize the expressive power of these language fragments in terms of both logics and tree patterns. Second, we investigate closure properties, focusing on the ability to perform basic Boolean operations while remaining within the fragment. We give a complete picture of the closure properties of these fragments, treating XPath expressions both as functions of arbitrary nodes in a document tree, and as functions that are applied only at the root of the tree. Finally, we provide sound and complete axiom systems and normal forms for several of these fragments. These results are useful for simplification of XPath expressions and optimization of XML queries.
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.