Vol.12 No.3&4 July 1, 2013

Topical Crawling on the Web through Local Site-Searches (pp203-214)
        Yaling Liu and Arvin Agah
In this paper, we investigate the feasibility of discovering topical resources by combining Web searches and local site-searches. Existing techniques of topical resource discovery consist of crawling the Web and searching the Web. The former typically analyses linkage among Web pages to estimate the relevance of an unseen document to a topic. The latter exploits the indices of generic search engines to discover documents relevant to a topic. Although the local site-search has been a simple and convenient feature of a Web site for human users to quickly locate desired information within the site that hosts tremendous number of documents, this feature has been ignored by the techniques of automatic topical resource discovery. A typical local site-search returns a list of titles, hyperlinks, and snippets of relevant documents, that can be used to estimate the relevance of the documents to the topic before actually fetching the documents. We propose an operational model to make use of this simple feature, and address how this model can be realized. Experiments have shown that this simple but efficient approach can provide much more precise estimations than a sophisticated intelligent topical crawler.

A Conceptual Graph Based Approach for Mappings among Multiple Fuzzy Ontologies (pp215-231)
        Lingyu Zhang, Yi Yan, and Z. M. Ma
Fuzzy ontology mapping is an important tool to solve the problem of interoperation among heterogeneous ontologies containing fuzzy information. At present, some researches have been done to expand existing mapping methods to deal with fuzzy ontology. However, these methods can not perform well when creating mappings among multiple fuzzy ontologies in a specific domain. To this end, this paper proposes a new method for fuzzy ontology mapping called FOM-CG (Fuzzy Ontology Mapping based on Conceptual Graph). To reduce unnecessary comparisons for multiple fuzzy ontologies in a domain, FOM-CG firstly creates or finds out a Reference Ontology that contains the most common and shared information. The other fuzzy ontologies in the domain are Source Ontologies. Then, these fuzzy ontologies are transformed into conceptual graph sets (i.e. R-set and S-sets). Next, some algorithms are presented to create mappings among conceptual graph sets. Finally, the obtained mappings are transformed into the mappings among fuzzy ontologies. Experimental results with some fuzzy ontologies from the real world indicate that FOM-CG performs encouragingly well.

A Model for Analysing DataPportal Performance: The Biodiversity Case (pp232-248)
        Pedro L.P. Corrêa, Pablo Salvanha, Antonio M. Saraiva, Paulo Scarpelini Neto, Carlos R. Valêncio and Rogeria C.G. de Souza
Currently, many museums, botanic gardens and herbariums keep data of biological collections and using computational tools researchers digitalize and provide access to their data using data portals. The replication of databases in portals can be accomplished through the use of protocols and data schema. However, the implementation of this solution demands a large amount of time, concerning both the transfer of fragments of data and processing data within the portal. With the growth of data digitalization in institutions, this scenario tends to be increasingly exacerbated, making it hard to maintain the records updated on the portals. As an original contribution, this research proposes analysing the data replication process to evaluate the performance of portals. The Inter-American Biodiversity Information Network (IABIN) biodiversity data portal of pollinators was used as a study case, which supports both situations: conventional data replication of records of specimen occurrences and interactions between them. With the results of this research, it is possible to simulate a situation before its implementation, thus predicting the performance of replication operations. Additionally, these results may contribute to future improvements to this process, in order to decrease the time required to make the data available in portals.

A Hybrid Approach Using PSO and K-Means for Semantic Clustering of Web Documents (pp249-264)
        J. Avanija and K. Ramar
With the massive growth and large volume of the web it is very difficult to recover results based on the user preferences. The next generation web architecture, semantic web reduces the burden of the user by performing search based on semantics instead of keywords. Even in the context of semantic technologies optimization problem occurs but rarely considered. In this paper Document clustering is applied to recover relevant documents. We propose a ontology based clustering algorithm using semantic similarity measure and Particle Swarm Optimization(PSO), which is applied to the annotated documents for optimizing the result. The proposed method uses Jena API and GATE tool API and the documents can be recovered based on their annotation features and relations. A preliminary experiment comparing the proposed method with K-Means shows that the proposed method is feasible and performs better than K-Means.

Slash-Based Relevance Propagation Model for Topic Distillation (pp265-290)
        Mohammad A. Golshani, Ali M. ZarehBidoki, and Vali Derhami
An efficient and effective ranking mechanism in the search engines remains as a challenging problem. In recent years, a few relevance propagation models like Hyperlink-based score propagation, Hyperlink-based term propagation, and Popularity-based propagation models have been proposed. In this paper, we will give a comprehensive study of the relevance propagation technologies for Web information retrieval and conduct both theoretical and experimental evaluations over these models to know which model is more effective and efficient. We also propose a new relevance propagation model based on content, link structure (web graph), and number of slashes in the URL. It propagates content and the number of slashes as scores through the link structure. The goal is to find more relevant web pages to the user query. To compare relevance propagation models, Letor 3.0- a standard web test collection- was used in the experiments. We have concluded that using number of slashes in the propagation process provides improvement in Web information retrieval accuracy.

A Secure Proxy-Based Cross-Domain Communication for Web Mashup (pp291-316)
        Shun-Wen Hsiao, Yeali S. Sun, and Meng Chang Chen
A web mashup is a web application that integrates content from heterogeneous sources to provide users with an integrated and seamless browsing experience. Client-side mashups differ from server-side mashups in that the content is integrated in the browser using the client-side scripts. However, the legacy same origin policy implemented by the current browsers cannot provide a flexible client-side communication mechanism to exchange information between resources from different sources. To address this problem, we propose a secure client-side cross-domain communication mechanism facilitated by a trusted proxy and the HTML 5 postMessage method. The proxy-based model supports fine-grained access control for elements that belong to different sources in web mashups; and the design guarantees the confidentiality, integrity, and authenticity during cross-domain communications. The proxy-based design also allows users to browse mashups without installing browser plug-ins. For mashups developers, the provided API minimizes the amount of code modification. The results of experiments demonstrate that the overhead incurred by our proxy model is low and reasonable. We anticipate the proxy-based design can help the mashup platform providers to provide a better solution to the mashup developers and users.

AlexandRIA: A Visual Tool for Generating Multi-device Rich Internet Applications (pp317-359)
        Luis O. Colombo-Mendoza, Giner Alor-Hernández, Alejandro Rodríguez-González and Ricardo Colomo-Palacios
Rich Internet Applications (RIAs) Engineering is an emerging area of Software Engineering, which still lacks of adequate development approaches and tools for support compared to Web Engineering. Therefore, in most cases the development of RIAs is performed in an ad-hoc manner and it is just driven by a set of new frameworks, which are mainly classified into JavaScript-based and non-JavaScript-based frameworks. RIAs development involves design principles of Web and desktop applications because RIAs, which are a new generation of Internet applications, combine behaviours and features of these two kinds of applications. Furthermore, mobile devices such as smartphones and tablet computers are also being involved in RIAs development because of the growing demand for ubiquitous Web 2.0 applications; therefore, RIAs are known as multi-device RIAs. During the last few years different contributions have arisen with the aim of bridging the gap between the Web and the RIAs engineering support. These proposals which are either: 1) extensions of existing methodologies for Web and hypermedia applications development, or 2) Model-driven Development (MDD) methods for rich Graphic User Interfaces (GUIs) designing, which do not cover multi-device RIAs development. Furthermore, some proposals lack of support tools. Taking this into account, in this paper we propose a visual tool that implements a GUI pattern-based approach for code generation of multi-device RIAs. This visual tool called AlexandRIA is a source and native code generator for Rapid Applications Development (RAD), which allows automatically generating code based on a set of preferences selected throughout a wizard. In order to validate our proposal, two cloud services APIs-based multi-device RIAs are generated using AlexandRIA. Finally, a qualitative/quantitative evaluation was performed in order to accurate the legitimacy of our proposal against other similar academic and commercial proposals.
 

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