Search results for: database query language

Authors: R. Gomathi, D. Sharmila

Abstract:

The emergence of the Semantic Web technology increases day by day due to the rapid growth of multiple web pages. Many standard formats are available to store the semantic web data. The most popular format is the Resource Description Framework (RDF). Querying large RDF graphs becomes a tedious procedure with a vast increase in the amount of data. The problem of query optimization becomes an issue in querying large RDF graphs. Choosing the best query plan reduces the amount of query execution time. To address this problem, nature inspired algorithms can be used as an alternative to the traditional query optimization techniques. In this research, the optimal query plan is generated by the proposed SAPSO algorithm which is a hybrid of Simulated Annealing (SA) and Particle Swarm Optimization (PSO) algorithms. The proposed SAPSO algorithm has the ability to find the local optimistic result and it avoids the problem of local minimum. Experiments were performed on different datasets by changing the number of predicates and the amount of data. The proposed algorithm gives improved results compared to existing algorithms in terms of query execution time.

Keywords: Semantic web, RDF, Query optimization, Nature inspired algorithms, PSO, SA.

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Authors: T.P. Andamuthu, Dr. P. Balasubramanie

Abstract:

The intermittent connectivity modifies the “always on" network assumption made by all the distributed query processing systems. In modern- day systems, the absence of network connectivity is considered as a fault. Since the last upload, it might not be feasible to transmit all the data accumulated right away over the available connection. It is possible that vital information may be delayed excessively when the less important information takes place of the vital information. Owing to the restricted and uneven bandwidth, it is vital that the mobile nodes make the most advantageous use of the connectivity when it arrives. Hence, in order to select the data that needs to be transmitted first, some sort of data prioritization is essential. A continuous query processing system for intermittently connected mobile networks that comprises of a delaytolerant continuous query processor distributed across the mobile hosts has been proposed in this paper. In addition, a mechanism for prioritizing query results has been designed that guarantees enhanced accuracy and reduced delay. It is illustrated that our architecture reduces the client power consumption, increases query efficiency by the extensive simulation results.

Keywords: Broadcast, Location, Mobile host, Mobility, Query.

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Authors: Jae Moon Lee

Abstract:

In general, algorithms to find continuous k-nearest neighbors have been researched on the location based services, monitoring periodically the moving objects such as vehicles and mobile phone. Those researches assume the environment that the number of query points is much less than that of moving objects and the query points are not moved but fixed. In gaming environments, this problem is when computing the next movement considering the neighbors such as flocking, crowd and robot simulations. In this case, every moving object becomes a query point so that the number of query point is same to that of moving objects and the query points are also moving. In this paper, we analyze the performance of the existing algorithms focused on location based services how they operate under gaming environments.

Keywords: Flocking behavior, heterogeneous agents, similarity, simulation.

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Authors: M. V. Sudhamani, C. R. Venugopal

Abstract:

Content-based Image Retrieval (CBIR) aims at searching image databases for specific images that are similar to a given query image based on matching of features derived from the image content. This paper focuses on a low-dimensional color based indexing technique for achieving efficient and effective retrieval performance. In our approach, the color features are extracted using the mean shift algorithm, a robust clustering technique. Then the cluster (region) mode is used as representative of the image in 3-D color space. The feature descriptor consists of the representative color of a region and is indexed using a spatial indexing method that uses *R -tree thus avoiding the high-dimensional indexing problems associated with the traditional color histogram. Alternatively, the images in the database are clustered based on region feature similarity using Euclidian distance. Only representative (centroids) features of these clusters are indexed using *R -tree thus improving the efficiency. For similarity retrieval, each representative color in the query image or region is used independently to find regions containing that color. The results of these methods are compared. A JAVA based query engine supporting query-by- example is built to retrieve images by color.

Keywords: Content-based, indexing, cluster, region.

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Authors: H. Ahmad, S. Kermanshahani, A. Simonet, M. Simonet

Abstract:

The data exchanged on the Web are of different nature from those treated by the classical database management systems; these data are called semi-structured data since they do not have a regular and static structure like data found in a relational database; their schema is dynamic and may contain missing data or types. Therefore, the needs for developing further techniques and algorithms to exploit and integrate such data, and extract relevant information for the user have been raised. In this paper we present the system OSIX (Osiris based System for Integration of XML Sources). This system has a Data Warehouse model designed for the integration of semi-structured data and more precisely for the integration of XML documents. The architecture of OSIX relies on the Osiris system, a DL-based model designed for the representation and management of databases and knowledge bases. Osiris is a viewbased data model whose indexing system supports semantic query optimization. We show that the problem of query processing on a XML source is optimized by the indexing approach proposed by Osiris.

Keywords: Data integration, semi-structured data, views, XML.

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Authors: Karim Heidari, Serajodin Katebi, Ali Reza Mahdavi Far

Abstract:

The purpose of this paper is to study Database Models to use them efficiently in E-commerce websites. In this paper we are going to find a method which can save and retrieve information in Ecommerce websites. Thus, semantic web applications can work with, and we are also going to study different technologies of E-commerce databases and we know that one of the most important deficits in semantic web is the shortage of semantic data, since most of the information is still stored in relational databases, we present an approach to map legacy data stored in relational databases into the Semantic Web using virtually any modern RDF query language, as long as it is closed within RDF. To achieve this goal we study XML structures for relational data bases of old websites and eventually we will come up one level over XML and look for a map from relational model (RDM) to RDF. Noting that a large number of semantic webs get advantage of relational model, opening the ways which can be converted to XML and RDF in modern systems (semantic web) is important.

Keywords: E-Commerce, Semantic Web, Database, XML, RDF.

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Authors: S. Banerjee

Abstract:

The paper describes design of an ontology in the financial domain for mutual funds. The design of this ontology consists of four steps, namely, specification, knowledge acquisition, implementation and semantic query. Specification includes a description of the taxonomy and different types mutual funds and their scope. Knowledge acquisition involves the information extraction from heterogeneous resources. Implementation describes the conceptualization and encoding of this data. Finally, semantic query permits complex queries to integrated data, mapping of these database entities to ontological concepts.

Keywords: Ontology, Semantic Web, Mutual Funds.

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Authors: Minsoo Lee, Yun-mi Kim, Yoon-kyung Lee

Abstract:

XML data consists of a very flexible tree-structure which makes it difficult to support the storing and retrieving of XML data. The node numbering scheme is one of the most popular approaches to store XML in relational databases. Together with the node numbering storage scheme, structural joins can be used to efficiently process the hierarchical relationships in XML. However, in order to process a tree-structured XPath query containing several hierarchical relationships and conditional sentences on XML data, many structural joins need to be carried out, which results in a high query execution cost. This paper introduces mechanisms to reduce the XPath queries including branch nodes into a much more efficient form with less numbers of structural joins. A two step approach is proposed. The first step merges duplicate nodes in the tree-structured query and the second step divides the query into sub-queries, shortens the paths and then merges the sub-queries back together. The proposed approach can highly contribute to the efficient execution of XML queries. Experimental results show that the proposed scheme can reduce the query execution cost by up to an order of magnitude of the original execution cost.

Keywords: XML, Xpath, tree-structured query, query reduction.

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Authors: Mohammed El Amine Abderrahim

Abstract:

Reformulating the user query is a technique that aims to improve the performance of an Information Retrieval System (IRS) in terms of precision and recall. This paper tries to evaluate the technique of query reformulation guided by an external resource for Arabic texts. To do this, various precision and recall measures were conducted and two corpora with different external resources like Arabic WordNet (AWN) and the Arabic Dictionary (thesaurus) of Meaning (ADM) were used. Examination of the obtained results will allow us to measure the real contribution of this reformulation technique in improving the IRS performance.

Keywords: Arabic NLP, Arabic Information Retrieval, Arabic WordNet, Query Expansion.

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Authors: Shohreh Ajoudanian, Mohammad Davarpanah Jazi

Abstract:

The rapid expansion of the web is causing the constant growth of information, leading to several problems such as increased difficulty of extracting potentially useful knowledge. Web content mining confronts this problem gathering explicit information from different web sites for its access and knowledge discovery. Query interfaces of web databases share common building blocks. After extracting information with parsing approach, we use a new data mining algorithm to match a large number of schemas in databases at a time. Using this algorithm increases the speed of information matching. In addition, instead of simple 1:1 matching, they do complex (m:n) matching between query interfaces. In this paper we present a novel correlation mining algorithm that matches correlated attributes with smaller cost. This algorithm uses Jaccard measure to distinguish positive and negative correlated attributes. After that, system matches the user query with different query interfaces in special domain and finally chooses the nearest query interface with user query to answer to it.

Keywords: Content mining, complex matching, correlation mining, information extraction.

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Authors: Abdelkader Dekdouk

Abstract:

In this paper we propose a novel approach for searching eCommerce products using a mobile phone, illustrated by a prototype eCoMobile. This approach aims to globalize the mobile search by integrating the concept of user multilinguism into it. To show that, we particularly deal with English and Arabic languages. Indeed the mobile user can formulate his query on a commercial product in either language (English/Arabic). The description of his information need on commercial products relies on the ontology that represents the conceptualization of the product catalogue knowledge domain defined in both English and Arabic languages. A query expressed on a mobile device client defines the concept that corresponds to the name of the product followed by a set of pairs (property, value) specifying the characteristics of the product. Once a query is submitted it is then communicated to the server side which analyses it and in its turn performs an http request to an eCommerce application server (like Amazon). This latter responds by returning an XML file representing a set of elements where each element defines an item of the searched product with its specific characteristics. The XML file is analyzed on the server side and then items are displayed on the mobile device client along with its relevant characteristics in the chosen language.

Keywords: Mobile computing, search engine, multilingualglobal eCommerce, ontology, XML.

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Authors: Laurent Thiry, Michel Hassenforder

Abstract:

This paper presents a general approach to implement efficient queries’ interpreters in a functional programming language. Indeed, most of the standard tools actually available use an imperative and/or object-oriented language for the implementation (e.g. Java for Jena-Fuseki) but other paradigms are possible with, maybe, better performances. To proceed, the paper first explains how to model data structures and queries in a functional point of view. Then, it proposes a general methodology to get performances (i.e. number of computation steps to answer a query) then it explains how to integrate some optimization techniques (short-cut fusion and, more important, data transformations). It then compares the functional server proposed to a standard tool (Fuseki) demonstrating that the first one can be twice to ten times faster to answer queries.

Keywords: Data transformation, functional programming, information server, optimization.

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Authors: Sarah Motiee, Azadeh Nematzadeh, Mehrnoush Shamsfard

Abstract:

Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques to extract phrases from documents and the query and doing stemming on words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done flexible and in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.

Keywords: Document ranking, Ontology, Spread activation algorithm, Annotation.

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Authors: Asmawi A., Affendey L. S., Udzir N. I., Mahmod R.

Abstract:

The topic of enhancing security in XML databases is important as it includes protecting sensitive data and providing a secure environment to users. In order to improve security and provide dynamic access control for XML databases, we presented XLog file to calculate user trust values by recording users’ bad transaction, errors and query severities. Severity-aware trust-based access control for XML databases manages the access policy depending on users' trust values and prevents unauthorized processes, malicious transactions and insider threats. Privileges are automatically modified and adjusted over time depending on user behaviour and query severity. Logging in database is an important process and is used for recovery and security purposes. In this paper, the Xlog file is presented as a dynamic and temporary log file for XML databases to enhance the level of security.

Keywords: XML database, trust-based access control, severity-aware, trust values, log file.

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Authors: Ei Ei Myat, Ni Lar Thein

Abstract:

With the tremendous growth of World Wide Web (WWW) data, there is an emerging need for effective information retrieval at the document level. Several query languages such as XML-QL, XPath, XQL, Quilt and XQuery are proposed in recent years to provide faster way of querying XML data, but they still lack of generality and efficiency. Our approach towards evolving a framework for querying semistructured documents is based on formal query algebra. Two elements are introduced in the proposed framework: first, a generic and flexible data model for logical representation of semistructured data and second, a set of operators for the manipulation of objects defined in the data model. In additional to accommodating several peculiarities of semistructured data, our model offers novel features such as bidirectional paths for navigational querying and partitions for data transformation that are not available in other proposals.

Keywords: Algebra, Semistructured data, Query Algebra.

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Authors: Mohib ur Rehman, Imran Ihsan, Mobin Uddin Ahmed, Nadeem Iftikhar, Muhammad Abdul Qadir

Abstract:

Multimedia, as it stands now is perhaps the most diverse and rich culture around the globe. One of the major needs of Multimedia is to have a single system that enables people to efficiently search through their multimedia catalogues. Many Domain Specific Systems and architectures have been proposed but up till now no generic and complete architecture is proposed. In this paper, we have suggested a generic architecture for Multimedia Database. The main strengths of our architecture besides being generic are Semantic Libraries to reduce semantic gap, levels of feature extraction for more specific and detailed feature extraction according to classes defined by prior level, and merging of two types of queries i.e. text and QBE (Query by Example) for more accurate yet detailed results.

Keywords: Multimedia Database Architecture, Semantics, Feature Extraction, Ontology.

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Authors: Alae El Alami, Mohamed Bahaj

Abstract:

This article discusses the passage of RDB to XML documents (schema and data) based on metadata and semantic enrichment, which makes the RDB under flattened shape and is enriched by the object concept. The integration and exploitation of the object concept in the XML uses a syntax allowing for the verification of the conformity of the document XML during the creation. The information extracted from the RDB is therefore analyzed and filtered in order to adjust according to the structure of the XML files and the associated object model. Those implemented in the XML document through a SQL query are built dynamically. A prototype was implemented to realize automatic migration, and so proves the effectiveness of this particular approach.

Keywords: RDB, XML, DTD, semantic enrichment.

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Authors: Hongzhi Wang, Jianzhong Li, Jizhou Luo

Abstract:

In many applications, data is in graph structure, which can be naturally represented as graph-structured XML. Existing queries defined on tree-structured and graph-structured XML data mainly focus on subgraph matching, which can not cover all the requirements of querying on graph. In this paper, a new kind of queries, topological query on graph-structured XML is presented. This kind of queries consider not only the structure of subgraph but also the topological relationship between subgraphs. With existing subgraph query processing algorithms, efficient algorithms for topological query processing are designed. Experimental results show the efficiency of implementation algorithms.

Keywords: XML, Graph Structure, Topological query.

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Authors: Ritwik Dutta, Marilyn Wolf

Abstract:

This paper describes the tradeoffs and the design from scratch of a self-contained, easy-to-use health dashboard software system that provides customizable data tracking for patients in smart homes. The system is made up of different software modules and comprises a front-end and a back-end component. Built with HTML, CSS, and JavaScript, the front-end allows adding users, logging into the system, selecting metrics, and specifying health goals. The backend consists of a NoSQL Mongo database, a Python script, and a SimpleHTTPServer written in Python. The database stores user profiles and health data in JSON format. The Python script makes use of the PyMongo driver library to query the database and displays formatted data as a daily snapshot of user health metrics against target goals. Any number of standard and custom metrics can be added to the system, and corresponding health data can be fed automatically, via sensor APIs or manually, as text or picture data files. A real-time METAR request API permits correlating weather data with patient health, and an advanced query system is implemented to allow trend analysis of selected health metrics over custom time intervals. Available on the GitHub repository system, the project is free to use for academic purposes of learning and experimenting, or practical purposes by building on it.

Keywords: Flask, Java, JavaScript, health monitoring, long term care, Mongo, Python, smart home, software engineering, webserver.

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Authors: Mehrnoush Shamsfard, Azadeh Nematzadeh, Sarah Motiee

Abstract:

Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques for extracting phrases and stemming words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.

Keywords: Document ranking, Ontology, Spread activation algorithm, Annotation.

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Authors: Bogdan Walek, Cyril Klimes

Abstract:

This paper focuses on testing database of existing information system. At the beginning we describe the basic problems of implemented databases, such as data redundancy, poor design of database logical structure or inappropriate data types in columns of database tables. These problems are often the result of incorrect understanding of the primary requirements for a database of an information system. Then we propose an algorithm to compare the conceptual model created from vague requirements for a database with a conceptual model reconstructed from implemented database. An algorithm also suggests steps leading to optimization of implemented database. The proposed algorithm is verified by an implemented prototype. The paper also describes a fuzzy system which works with the vague requirements for a database of an information system, procedure for creating conceptual from vague requirements and an algorithm for reconstructing a conceptual model from implemented database.

Keywords: testing, database, relational database, information system, conceptual model, fuzzy, uncertain information, database testing, reconstruction, requirements, optimization

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Authors: Sharjeel Aslam, Vassil Vassilev, Karim Ouazzane

Abstract:

Ontologies and various semantic repositories became a convenient approach for implementing model-driven architectures of distributed systems on the Web. SPARQL is the standard query language for querying such. However, although SPARQL is well-established standard for querying semantic repositories in RDF and OWL format and there are commonly used APIs which supports it, like Jena for Java, its parallel option is not incorporated in them. This article presents a complete framework consisting of an object algebra for parallel RDF and an index-based implementation of the parallel query engine capable of dealing with the distributed RDF ontologies which share common vocabulary. It has been implemented in Java, and for validation of the algorithms has been applied to the problem of organizing virtual exhibitions on the Web.

Keywords: Distributed ontologies, parallel querying, semantic indexing, shared vocabulary, SPARQL.

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Authors: Meltem Serhatli, Ferda N. Alpaslan

Abstract:

Processing the data by computers and performing reasoning tasks is an important aim in Computer Science. Semantic Web is one step towards it. The use of ontologies to enhance the information by semantically is the current trend. Huge amount of domain specific, unstructured on-line data needs to be expressed in machine understandable and semantically searchable format. Currently users are often forced to search manually in the results returned by the keyword-based search services. They also want to use their native languages to express what they search. In this paper, an ontology-based automated question answering system on software test documents domain is presented. The system allows users to enter a question about the domain by means of natural language and returns exact answer of the questions. Conversion of the natural language question into the ontology based query is the challenging part of the system. To be able to achieve this, a new algorithm regarding free text to ontology based search engine query conversion is proposed. The algorithm is based on investigation of suitable question type and parsing the words of the question sentence.

Keywords: Description Logics, ontology, question answering, reasoning.

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Authors: Yogesh Gupta, Ashish Saini, A.K. Saxena

Abstract:

Information retrieval has become an important field of study and research under computer science due to explosive growth of information available in the form of full text, hypertext, administrative text, directory, numeric or bibliographic text. The research work is going on various aspects of information retrieval systems so as to improve its efficiency and reliability. This paper presents a comprehensive study, which discusses not only emergence and evolution of information retrieval but also includes different information retrieval models and some important aspects such as document representation, similarity measure and query expansion.

Keywords: Information Retrieval, query expansion, similarity measure, query expansion, vector space model.

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Authors: Mawloud Mosbah, Bachir Boucheham

Abstract:

We present here the results for a comparative study of some techniques, available in the literature, related to the relevance feedback mechanism in the case of a short-term learning. Only one method among those considered here is belonging to the data mining field which is the K-nearest neighbors algorithm (KNN) while the rest of the methods is related purely to the information retrieval field and they fall under the purview of the following three major axes: Shifting query, Feature Weighting and the optimization of the parameters of similarity metric. As a contribution, and in addition to the comparative purpose, we propose a new version of the KNN algorithm referred to as an incremental KNN which is distinct from the original version in the sense that besides the influence of the seeds, the rate of the actual target image is influenced also by the images already rated. The results presented here have been obtained after experiments conducted on the Wang database for one iteration and utilizing color moments on the RGB space. This compact descriptor, Color Moments, is adequate for the efficiency purposes needed in the case of interactive systems. The results obtained allow us to claim that the proposed algorithm proves good results; it even outperforms a wide range of techniques available in the literature.

Keywords: CBIR, Category Search, Relevance Feedback (RFB), Query Point Movement, Standard Rocchio’s Formula, Adaptive Shifting Query, Feature Weighting, Optimization of the Parameters of Similarity Metric, Original KNN, Incremental KNN.

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Authors: R.Anita, V.Ganga Bharani, N.Nityanandam, Pradeep Kumar Sahoo

Abstract:

The explosive growth of World Wide Web has posed a challenging problem in extracting relevant data. Traditional web crawlers focus only on the surface web while the deep web keeps expanding behind the scene. Deep web pages are created dynamically as a result of queries posed to specific web databases. The structure of the deep web pages makes it impossible for traditional web crawlers to access deep web contents. This paper, Deep iCrawl, gives a novel and vision-based approach for extracting data from the deep web. Deep iCrawl splits the process into two phases. The first phase includes Query analysis and Query translation and the second covers vision-based extraction of data from the dynamically created deep web pages. There are several established approaches for the extraction of deep web pages but the proposed method aims at overcoming the inherent limitations of the former. This paper also aims at comparing the data items and presenting them in the required order.

Keywords: Crawler, Deep web, Web Database

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Authors: Kee-Leong Tan, Karyn Wei-Ju Khoo, Hui-Na Chua

Abstract:

Service discovery is a very important component of Service Oriented Architectures (SOA). This paper presents two alternative approaches to customise the query results of private service registry such as Universal Description, Discovery and Integration (UDDI). The customisation is performed based on some pre-defined and/or real-time changing parameters. This work identifies the requirements, designs and additional mechanisms that must be applied to UDDI in order to support this customisation capability. We also detail the implements of the approaches and examine its performance and scalability. Based on our experimental results, we conclude that both approaches can be used to customise registry query results, but by storing personalization parameters in external resource will yield better performance and but less scalable when size of query results increases. We believe these approaches when combined with semantics enabled service registry will enhance the service discovery methods within a private UDDI registry environment.

Keywords: Service Oriented Architecture (SOA), Web service, Service discovery, registry, UDDI

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Authors: Boontita Suchyukorn, Raweewan Auepanwiriyakul

Abstract:

A Data Warehouses is a repository of information integrated from source data. Information stored in data warehouse is the form of materialized in order to provide the better performance for answering the queries. Deciding which appropriated views to be materialized is one of important problem. In order to achieve this requirement, the constructing search space close to optimal is a necessary task. It will provide effective result for selecting view to be materialized. In this paper we have proposed an approach to reoptimize Multiple View Processing Plan (MVPP) by using global common subexpressions. The merged queries which have query processing cost not close to optimal would be rewritten. The experiment shows that our approach can help to improve the total query processing cost of MVPP and sum of query processing cost and materialized view maintenance cost is reduced as well after views are selected to be materialized.

Keywords: Data Warehouse, materialized views, query rewriting, common subexpressions.

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Authors: Norjihan Abdul Ghani, Zailani Mohd Sidek

Abstract:

Nowadays, organizations and business has several motivating factors to protect an individual-s privacy. Confidentiality refers to type of sharing information to third parties. This is always referring to private information, especially for personal information that usually needs to keep as a private. Because of the important of privacy concerns today, we need to design a database system that suits with privacy. Agrawal et. al. has introduced Hippocratic Database also we refer here as a privacy-aware database. This paper will explain how HD can be a future trend for web-based application to enhance their privacy level of trustworthiness among internet users.

Keywords: Hippocratic database, privacy, privacy-aware.

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Authors: Richard Elling Moe

Abstract:

Computer languages are usually lumped together into broad -paradigms-, leaving us in want of a finer classification of kinds of language. Theories distinguishing between -genuine differences- in language has been called for, and we propose that such differences can be observed through a notion of expressive mode. We outline this concept, propose how it could be operationalized and indicate a possible context for the development of a corresponding theory. Finally we consider a possible application in connection with evaluation of language revision. We illustrate this with a case, investigating possible revisions of the relational algebra in order to overcome weaknesses of the division operator in connection with universal queries.

Keywords: Expressive mode, Computer language species, Evaluation of revision, Relational algebra, Universal database queries

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