Web Service Retrieval by Structured Models

Much of the information available on theWorldWideWeb cannot effectively be found by the help of search engines because the information is dynamically generated on a user’s request.This applies to online decision support services as well as Deep Web information. We present in this paper a retrieval system that uses a variant of structured modeling to describe such information services, and similarity of models for retrieval. The computational complexity of the similarity problem is discussed, and graph algorithms for retrieval on repositories of service descriptions are introduced. We show how bounds for combinatorial optimization problems can provide filter algorithms in a retrieval context. We report about an evaluation of the retrieval system in a classroom experiment and give computational results on a benchmark library.Economics ;

Embedding Web-based Statistical Translation Models in Cross-Language Information Retrieval

Although more and more language pairs are covered by machine translation services, there are still many pairs that lack translation resources. Cross-language information retrieval (CLIR) is an application which needs translation functionality of a relatively low level of sophistication since current models for information retrieval (IR) are still based on a bag-of-words. The Web provides a vast resource for the automatic construction of parallel corpora which can be used to train statistical translation models automatically. The resulting translation models can be embedded in several ways in a retrieval model. In this paper, we will investigate the problem of automatically mining parallel texts from the Web and different ways of integrating the translation models within the retrieval process. Our experiments on standard test collections for CLIR show that the Web-based translation models can surpass commercial MT systems in CLIR tasks. These results open the perspective of constructing a fully automatic query translation device for CLIR at a very low cost.Comment: 37 page

An Integrated Information Retrieval Framework for Managing the Digital Web Ecosystem

The information explosion makes the digital Web ecosystem exploration, as a valid web search tool challenging for retrieving relevant information and knowledge. The existing tools are not integrated, and search results are not well managed. In this article, we describe effective information retrieval services for users and agents in various digital ecosystem scenarios. A novel integrated information retrieval framework (IIRF) is proposed, which employs the Web search technologies and traditional database searching techniques to provide comprehensive, dynamic, personalized, and organization-oriented information retrieval services, ranging from the Internet, intranet, to personal desktop. Experiments are carried out demonstrating the improvements in the search process with an average precision of Web search results to standard 11 recall level, attaining improvement from 41.7% of a comparable system to 65.2% of search. A 23.5% precision improvement is achieved with the framework. The comparison made among search engines presents a similar development with satisfactory search results

Web service searching

With the growing number of Web services, it is no longer adequate to locate a Web service by searching its name or browsing a UDDI directory. An efficient Web services discovery mechanism is necessary for locating and selecting the required Web services. Searching mechanism should be based on Web service description rather than on keywords. In this work, we introduce a Web service searching prototype that can locate Web services by comparing all available information encoded in Web service description, such as operation name, input and output types, the structure of the underlying XML schema, and the semantic of element names. Our approach combines information-retrieval techniques, weighted bipartite graph matching algorithm and tree-matching algorithm. Given a query, represented as set of keywords, Web service description, or operation description, an information retrieval technique is used to rank the candidate Web services based on their text-base similarity to the query. The ranked result can be further refined by computing their structure similarity. (Abstract shortened by UMI.) Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .J34. Source: Masters Abstracts International, Volume: 44-03, page: 1403. Thesis (M.Sc.)--University of Windsor (Canada), 2005

Folksonomies : Indexing and Retrieval in Web 2.0

One of the defining principles of Web 2.0 when it first emerged was that the collective intelligence of users should be harnessed in order to enrich services for that user community (O’Reilly, 2005). This so-called ‘network effect’ principle remains as central to the Web 2.0 thesis then as it does five years on (O’Reilly and Battelle, 2009). Folksonomies, or collaborative tagging systems, have become the epitome of the network effect; using collective intelligence to organise and retrieve information on the Web. In Folksonomies: indexing and retrieval in Web 2.0, author Isabella Peters explores the use of folksonomies in ‘collaborative information services’, a catch-all term used by Peters to encompass the heterogeneous nature of the Web 2.0 services that use tagging systems. The stated purpose of Folksonomies is to provide a degree of insight into folksonomy applications, as well as discuss their strengths, weaknesses and how their problems can be ameliorated by applying recognised information retrieval models and formal knowledge representation methods

An integrating text retrieval framework for Digital Ecosystems Paradigm

The purpose of the research is to provide effective information retrieval services for digital ?organisms? in a digital ecosystem by leveraging the power of Web searching technology. A novel integrating digital ecosystem search framework (a new digital organism) is proposed which employs the Web search technology and traditional database searching techniques to provide economic organisms with comprehensive, dynamic, and organization-oriented information retrieval ranging from the Internet to personal (semantic) desktop

Binary Particle Swarm Optimization based Biclustering of Web usage Data

Web mining is the nontrivial process to discover valid, novel, potentially useful knowledge from web data using the data mining techniques or methods. It may give information that is useful for improving the services offered by web portals and information access and retrieval tools. With the rapid development of biclustering, more researchers have applied the biclustering technique to different fields in recent years. When biclustering approach is applied to the web usage data it automatically captures the hidden browsing patterns from it in the form of biclusters. In this work, swarm intelligent technique is combined with biclustering approach to propose an algorithm called Binary Particle Swarm Optimization (BPSO) based Biclustering for Web Usage Data. The main objective of this algorithm is to retrieve the global optimal bicluster from the web usage data. These biclusters contain relationships between web users and web pages which are useful for the E-Commerce applications like web advertising and marketing. Experiments are conducted on real dataset to prove the efficiency of the proposed algorithms

Fast Information Retrieval in the Open Grid Service Architecture

Information retrieval offers resource discovery mechanisms for unstructured information and has thus been identified as a standardization goal by the open grid forum. We argue that an integration of information retrieval into the infrastructure is not only an interesting prospect for grid users, but is in fact necessary because the batch processing approach supported by the open grid service architecture is at odds with the requirements of online query processing. The cost of staging the search indices to an allocated compute node to answer sporadic but frequent search queries is prohibitive. We advocate the use of web services as a cross site messaging mechanism and discuss the alternatives. To investigate, we have designed and built a prototype system for grid image retrieval. Unfortunately, the statelessness and isolation of web services proved problematic for our purposes, but we present a software architecture that can efficiently overcome these issues

An QoS based multifaceted matchmaking framework for web services discovery

With the increasing demand, the web service has been the prominent technology for providing good solutions to the interoperability of different kind of systems. Web service supports mainly interoperability properties as it is the major usage of this promising technology. Although several technologies had been evolved before web service technology and this has more advantage of other technologies. This paper has concentrated mainly on the Multifaceted Matchmaking framework for Web Services Discovery using Quality of Services parameters. Traditionally web services have been discovered only with the functional properties like input, output, precondition and effect. Nowadays there is an increase in number of service providers leads to increase in the web services with same functionality. So user need to discover the best services so Quality of Service factors has been evolved. The traditional discovery supports only few quality parameters and so the discovery is easy in retrieval of services. As the parameter increases the matchmaking will be complex during service discovery. So in this proposed work, we have identified 21 QoS parameters which are suitable for service discovery. The information retrieval techniques are used to evaluate the results and results show that the proposed framework is better