A coherent query language for XML

Text search engines are inadequate for indexing and searching XML documents because they ignore metadata and aggregation structure implicit in the XML documents. On the other hand, the query languages supported by specialized XML search engines are very complex. In this paper, we present a simple yet flexible query language, and develop its semantics to enable intuitively appealing extraction of relevant fragments of information while simultaneously falling back on retrieval through plain text search if necessary. Our approach combines and generalizes several available techniques to obtain precise and coherent results.

Using a relational database for scalable XML search

XML is a flexible and powerful tool that enables information and security sharing in heterogeneous environments. Scalable technologies are needed to effectively manage the growing volumes of XML data. A wide variety of methods exist for storing and searching XML data; the two most common techniques are conventional tree-based and relational approaches. Tree-based approaches represent XML as a tree and use indexes and path join algorithms to process queries. In contrast, the relational approach utilizes the power of a mature relational database to store and search XML. This method relationally maps XML queries to SQL and reconstructs the XML from the database results. To date, the limited acceptance of the relational approach to XML processing is due to the need to redesign the relational schema each time a new XML hierarchy is defined. We, in contrast, describe a relational approach that is fixed schema eliminating the need for schema redesign at the expense of potentially longer runtimes. We show, however, that these potentially longer runtimes are still significantly shorter than those of the tree approach. We use a popular XML benchmark to compare the scalability of both approaches. We generated large collections of heterogeneous XML documents ranging in size from 500 MB to 8 GB using the XBench benchmark. The scalability of each method was measured by running XML queries that cover a wide range of XML search features on each collection. We measure the scalability of each method over different query features as the collection size increases. In addition, we examine the performance of each method as the result size and the number of predicates increase. Our results show that our relational approach provides a scalable approach to XML retrieval by leveraging existing relational database optimizations. Furthermore, we show that the relational approach typically outperforms the tree-based approach while scaling consistently over all collections studied.

RRSi: indexing XML data for proximity twig queries

Twig query pattern matching is a core operation in XML query processing. Indexing XML documents for twig query processing is of fundamental importance to supporting effective information retrieval. In practice, many XML documents on the web are heterogeneous and have their own formats; documents describing relevant information can possess different structures. Therefore some “user-interesting” documents having similar but non-exact structures against a user query are often missed out. In this paper, we propose the RRSi, a novel structural index designed for structure-based query lookup on heterogeneous sources of XML documents supporting proximate query answers. The index avoids the unnecessary processing of structurally irrelevant candidates that might show good content relevance. An optimized version of the index, oRRSi, is also developed to further reduce both space requirements and computational complexity. To our knowledge, these structural indexes are the first to support proximity twig queries on XML documents. The results of our preliminary experiments show that RRSi and oRRSi based query processing significantly outperform previously proposed techniques in XML repositories with structural heterogeneity.

Improving the definition of general constraints in UML

An important aspect in the specification of conceptual schemas is the definition of general constraints that cannot be expressed by the predefined constructs provided by conceptual modeling languages. This is generally achieved by using general-purpose languages like OCL. In this paper we propose a new approach that facilitates the definition of such general constraints in UML. More precisely, we define a profile that extends the set of predefined UML constraints by adding certain types of constraints that are commonly used in conceptual schemas. We also show how our proposal facilitates reasoning about the constraints and their automatic code generation, study the application of our ideas to the specification of two real-life applications, and present a prototype tool implementation.

XFlavor: providing XML features in media representation

We present XFlavor, a framework for providing XML representation of multimedia data. XFlavor can be used to convert multimedia data back and forth between binary and XML representations. Compared to bitstreams, XML documents are easier to access and manipulate, and consequently, the development of multimedia processing software is greatly facilitated, as one generic XML parser can be used to read and write different types of data in XML form.

Logical Representation of a Conceptual Model for Spatial Data Warehouses

The MultiDimER model is a conceptual model used for representing a multidimensional view of data for Data Warehouse (DW) and On-Line Analytical Processing (OLAP) applications. This model includes a spatial extension allowing spatiality in levels, hierarchies, fact relationships, and measures. In this way decision-making users can represent in an abstract manner their analysis needs without considering complex implementation issues and spatial OLAP tools developers can have a common vision for representing spatial data in a multidimensional model. In this paper we propose the transformation of a conceptual schema based on the MultiDimER constructs to an object-relational schema. We based our mapping on the SQL:2003 and SQL/MM standards giving examples of commercial implementation using Oracle 10g with its spatial extension. Further we use spatial integrity constraints to ensure the semantic equivalence of the conceptual and logical schemas. We also show some examples of Oracle spatial functions, including aggregation functions required for the manipulation of spatial data. The described mappings to the object-relational model along with the examples using a commercial system show the feasibility of implementing spatial DWs in current commercial DBMSs. Further, using integrated architectures, where spatial and thematic data is defined within the same DBMS, facilitates the system management simplifying data definition and manipulation.

XMLNET: An Architecture for Cost Effective Network Management Based on XML Technologies

XML technologies have been recently introduced in network management towards alleviating limitations of SNMP. The XML W3C standard, along with XML technologies has the potential to boost open, interoperable, cost-effective and standards-based management solutions. This paper highlights recent efforts towards XML network management and introduces an architecture supporting XML-based network management applications. This architecture specifies a runtime environment that parses XML documents containing composite operations for individual devices, as well as for heterogeneous mutli-vendor networks. Management operations in the scope of XML documents are defined in a programmable fashion based on an XML-based composition language supporting aggregations of elementary operations, looping commands, conditional statements, as well as simple rules signifying the occurrence of specific events. The introduced environment allows network managers to define management operations featuring high-level semantics and accordingly produce sophisticated applications through XML authoring. Following the illustration of the architecture, its composition language and issues relating to security and error handling, the paper ends up presenting a prototype implementation, along with associated performance evaluation results.

Language resources for Hebrew

We describe a suite of standards, resources and tools for computational encoding and processing of Modern Hebrew texts. These include an array of XML schemas for representing linguistic resources; a variety of text corpora, raw, automatically processed and manually annotated; lexical databases, including a broad-coverage monolingual lexicon, a bilingual dictionary and a WordNet; and morphological processors which can analyze, generate and disambiguate Hebrew word forms. The resources are developed under centralized supervision, so that they are compatible with each other. They are freely available and many of them have already been used for several applications, both academic and industrial.

Regia: a metadata editor for audiovisual documents

Although the Metadata Editor is an important part of any digital library, it becomes fundamental in the presence of audiovisual content. This is because the metadata produced by automated support tools (such as speech recognizers and shot detection procedures) is error-prone and often needs correction. In addition, scenes are manually annotated. This paper describes Regia, a prototype application for manually editing metadata for audiovisual documents developed in the ECHO project. Regia allows the user to manually edit textual metadata and to hierarchically organize the segmentation of the audiovisual content. An important feature of this metadata editor is that it is not hard-wired with a particular metadata attributes set. To achieve this feature the XML schema of the metadata model is used by the editor as a configuration file.

Learning element similarity matrix for semi-structured document analysis

Capturing latent structural and semantic properties in semi-structured documents (e.g., XML documents) is crucial for improving the performance of related document analysis tasks. Structured Link Vector Mode (SLVM) is a representation recently proposed for modeling semi-structured documents. It uses an element similarity matrix to capture the latent relationships between XML elements—the constructing components of an XML document. In this paper, instead of applying heuristics to define the element similarity matrix, we propose to compute the matrix using the machine learning approach. In addition, we incorporate term semantics into SLVM using latent semantic indexing to enhance the model accuracy, with the element similarity learnability property preserved. For performance evaluation, we applied the similarity learning to k-nearest neighbors search and similarity-based clustering, and tested the performance using two different XML document collections. The SLVM obtained via learning was found to outperform significantly the conventional Vector Space Model and the edit-distance-based methods. Also, the similarity matrix, obtained as a by-product, can provide higher-level knowledge on the semantic relationships between the XML elements.

Supporting ordering and consistency in a distributed Event Heap for Ubiquitous Computing

The Stanford Event Heap has been shown to provide appropriate support for constructing interactive workspace applications. Given this success it is natural to consider the Event Heap as a platform to support other classes of Ubiquitous Computing applications. In this paper we argue that the distributed, spontaneous nature of these applications places additional demands on the Event Heap that require extensions to both the engineering and API. Suitable extensions are described and their use to support a typical Ubicomp application is discussed.

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Approximate schemas,source-consistency and query answering

We use the Edit distance with Moves on words and trees and say that two regular (tree) languages are ε-close if every word (tree) of one language is ε-close to the other. A transducer model is introduced to compare tree languages (schemas) with different alphabets and attributes. Using the statistical embedding of Fischer et al. (Proceedings of 21st IEEE Symposium on Logic in Computer Science, pp. 421–430, 2006), we show that Source-Consistency and Approximate Query Answering are testable on words and trees, i.e. can be approximately decided within ε by only looking at a constant fraction of the input.

Methods for quantitative usability requirements: a case study on the development of the user interface of a mobile phone

Quantitative usability requirements are a critical but challenging, and hence an often neglected aspect of a usability engineering process. A case study is described where quantitative usability requirements played a key role in the development of a new user interface of a mobile phone. Within the practical constraints of the project, existing methods for determining usability requirements and evaluating the extent to which these are met, could not be applied as such, therefore tailored methods had to be developed. These methods and their applications are discussed.

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Interacting with mobile services: an evaluation of camera-phones and visual tags

We present a study of using camera-phones and visual-tags to access mobile services. Firstly, a user-experience study is described in which participants were both observed learning to interact with a prototype mobile service and interviewed about their experiences. Secondly, a pointing-device task is presented in which quantitative data was gathered regarding the speed and accuracy with which participants aimed and clicked on visual-tags using camera-phones. We found that participants’ attitudes to visual-tag-based applications were broadly positive, although they had several important reservations about camera-phone technology more generally. Data from our pointing-device task demonstrated that novice users were able to aim and click on visual-tags quickly (well under 3 s per pointing-device trial on average) and accurately (almost all meeting our defined speed/accuracy tradeoff of 6% error-rate). Based on our findings, design lessons for camera-phone and visual-tag applications are presented.

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Rapid prototyping of social group dynamics in multiagent systems

In this article we present an engineering approach for the integration of social group dynamics in the behavior modeling of multiagent systems. To this end, a toolbox was created that brings together several theories from the social sciences, each focusing on different aspects of group dynamics. Due to its modular approach, the toolbox can either be used as a central control component of an application or it can be employed temporarily to rapidly test the feasibility of the incorporated theories for a given application domain. This is exemplified by applying the toolbox to different applications.

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EXEM: Efficient XML data exchange management for mobile applications

In the past decade, the number of mobile devices has increased significantly. These devices are in turn showing more computational capabilities. It is therefore possible to envision a near future where client applications may be deployed on these devices. There are, however, constraints that hinder this deployment, especially the limited communication bandwidth and storage space available. This paper describes the Efficient XML Data Exchange Manager (EXEM) that combines context-dependent lossy and lossless compression mechanisms used to support lightweight exchange of objects in XML format between server and client applications. The lossy compression mechanism reduces the size of XML messages by using known information about the application. The lossless compression mechanism decouples data and metadata (compression dictionary) content. We illustrate the use of EXEM with a prototype implementation of the lossless compression mechanism that shows the optimization of the available resources on the server and the mobile client. These experimental results demonstrate the efficiency of the EXEM approach for XML data exchange in the context of mobile application development.

The 2007 IEEE CEC simulated car racing competition

This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process, we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competition.

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ODAP: an ontological approach for expressing the semantics of analysis patterns in conceptual modeling

Systematic software reuse is emerging as a promising route to improved software development productivity and quality. While many benefits of patterns reuse have been identified, there is a need to develop a mechanism for supporting and automating the reuse of relevant analysis patterns for conceptual modeling. To enable effective reuse of analysis patterns, extant approaches require judgment about correctly instantiating and combining the analysis patterns. Building on prior research in ontology and conceptual modeling, we propose a “top-down” approach, referred to as Ontology for Describing Analysis Patterns (ODAP), to explicitly express the semantics of analysis patterns. We show how ODAP helps provide a mechanism to identify appropriate instances of analysis patterns including the discovery of valid combinations with other patterns in a patterns base. Thus, ODAP can enable communication of the meaning of the analysis pattern constructs to modelers and be the basis for a design support environment that supports the development of conceptual schemas using analysis patterns.

Bayesian network based business information retrieval model

The quality of business information can significantly affect the operation level of enterprise. This paper analyses the problem of business information retrieval (BIR). A Bayesian Network Based business information retrieval model (BN-BIRM) is proposed by means of Bayesian network (BN) and information retrieval (IR) theory and a method for query adaptation is presented. In this model the customized query requirement of enterprise (CQR) is expressed in terms of the predefined illustrative documents related to business domain. The similarities between the documents and the query are evaluated with the conditional probabilities among the nodes in the BN. In the experiments, BN-BIRM is compared with the Belief Network model based on vector space model (VSM) ranking strategy and the Inference Network model based on TF-IDF ranking strategy. The experimental results show that BN-BIRM is effective for collecting business information on a large scale.

Innovations in Individual Feature History Management—The Significance of Feature-based Temporal Model

A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO’s temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO’s temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure.