REDUCING DISTRIBUTED URLS CRAWLING TIME : A COMPARISON OF GUIDS AND IDS

Web crawler visits websites for the purpose of indexing. The dynamic nature of today’s web makes the crawling process harder than before as web contents are continuously updated. In addition, crawling speed is important considering tsunami of big data that need to be indexed among competitive search engines. This research project is aimed to provide survey of current problems in distributed web crawlers. It then investigate the best crawling speed between dynamic globally unique identifiers (GUIDs) and the traditional static identifiers (IDs). Experiment are done by implementing Arachnot.net web crawlers to index up to 20000 locally generated URLs using both techniques. The results shown that URLs crawling time can be reduced up to 7% by using GUIDs technique instead of using IDs

Design of Human Powered Directories using Mobile Agents

ABSTRACT The Internet is a worldwide mechanism for information dissemination, a medium for collaboration and communication between individuals and their computers from local to global scope. Web is a system of interlinked hypertext documents accessed via Internet. Web contains billions of visible pages and it is not easy for a user to search for a specific web page. Search Engines help users to search for specific web page out of huge collection of pages. Human powered directories depend on humans to create a repository. In this paper we present use of mobile agents in designing Human powered directories

DOL - an Interoperable Document Server

We describe the design and expierences gained with the database and web-based document server DOL, which we developed at the University of Leipzig (http://dol.uni-leipzig.de). The server provides a central repository for a variety of fulltext documents. In Leipzig, it has been used since 1998 as a university-wide digital library for documents by local authors, in particular Ph.D. theses, master theses, research papers, lecture notes etc., offering a central access point to the university´s research results and educational material. Decentralized administration and different workflows are supported to met organizational and legal requirements of specific document types (e.g., Ph.D. theses). All documents are converted into several formats, and can be downloaded or viewed online in a page-wise fashion. The documents are searchable in a flexible way using fulltext and bibliographic queries. Moreover, a multi-level navigation interface is provided, supporting browsing along several dimentions. DOL is interoperable with global digital libraries such as NCSTRL and can be ported to the needs of different organisations. It is also in use at Stanford University

Building a scalable index and a web search engine for music on the Internet using Open Source software

The Internet has made possible the access to thousands of freely available music tracks with Creative Commons or Public Domain licenses. Actually, this number keeps growing every year. In practical terms, it is very difficult to browse this music collection, because it is wide and disperse in hundreds of websites. To address the music recommendation issue, a case study on existing systems was made, to put the problem in context in order to identify necessary building blocks. This thesis is mainly focused on the problem of indexing this large collection of music. The reason to focus on this problem, is that there is no database or index holding information about this music material, thus making this research on the subject extremely difficult. In order to figure out what software could help solve this problem, the state of the art in “Open Source tools for web crawling and indexing” was assessed. Based on the conclusions from the state of the art, a prototype was developed and implemented using the most appropriate software framework. The created solution proved it was capable of crawling the web pages, while parsing and indexing MP3 files. The produced index is available through a web search engine interface also producing results in XML format. The results obtained lead to the conclusion that it is attainable to build a scalable index and web search engine for music in the Internet using Open Source software. This is supported by the proof of concept achieved with the working prototype.A Internet tornou possível o acesso a milhares de faixas musicais disponíveis gratuitamente segundo uma licença Creative Commons ou de Domínio Público. Na realidade, este número continua a aumentar em cada ano. Em termos práticos, é muito difícil navegar nesta colecção de música, pois a mesma é vasta e encontra-se dispersa em milhares de sites na Web. Para abordar o assunto da recomendação de música, um caso de estudo sobre sistemas de recomendação de música existentes foi elaborado, para contextualizar o problema e identificar os grandes blocos que os constituem. Esta tese foca-se na problemática da indexação de uma grande colecção de música, pela razão de que, não existe uma base de dados ou índice que contenha informação sobre este repositório musical, tornando muito difícil o estudo nesta matéria. De forma a compreender que software poderia ajudar a resolver o problema, foi avaliado o estado da arte em ferramentas de rastreio de conteúdos web e indexação de código aberto. Com base nas conclusões do estado da arte, o protótipo foi desenvolvido e implementado, utilizando o software mais apropriado para a tarefa. A solução criada provou que era possível percorrer as páginas Web, enquanto se analisavam e indexavam MP3. O índice produzido encontra-se disponível através de um motor de busca online e também com resultados no formato XML. Os resultados obtidos levam a concluir que é possível, construir um índice escalável e motor de busca na web para música na Internet utilizando software Open Source. Estes resultados são fundamentados pela prova de conceito obtida com o protótipo funcional

A customized semantic service retrieval methodology for the digital ecosystems environment

With the emergence of the Web and its pervasive intrusion on individuals, organizations, businesses etc., people now realize that they are living in a digital environment analogous to the ecological ecosystem. Consequently, no individual or organization can ignore the huge impact of the Web on social well-being, growth and prosperity, or the changes that it has brought about to the world economy, transforming it from a self-contained, isolated, and static environment to an open, connected, dynamic environment. Recently, the European Union initiated a research vision in relation to this ubiquitous digital environment, known as Digital (Business) Ecosystems. In the Digital Ecosystems environment, there exist ubiquitous and heterogeneous species, and ubiquitous, heterogeneous, context-dependent and dynamic services provided or requested by species. Nevertheless, existing commercial search engines lack sufficient semantic supports, which cannot be employed to disambiguate user queries and cannot provide trustworthy and reliable service retrieval. Furthermore, current semantic service retrieval research focuses on service retrieval in the Web service field, which cannot provide requested service retrieval functions that take into account the features of Digital Ecosystem services. Hence, in this thesis, we propose a customized semantic service retrieval methodology, enabling trustworthy and reliable service retrieval in the Digital Ecosystems environment, by considering the heterogeneous, context-dependent and dynamic nature of services and the heterogeneous and dynamic nature of service providers and service requesters in Digital Ecosystems.The customized semantic service retrieval methodology comprises: 1) a service information discovery, annotation and classification methodology; 2) a service retrieval methodology; 3) a service concept recommendation methodology; 4) a quality of service (QoS) evaluation and service ranking methodology; and 5) a service domain knowledge updating, and service-provider-based Service Description Entity (SDE) metadata publishing, maintenance and classification methodology.The service information discovery, annotation and classification methodology is designed for discovering ubiquitous service information from the Web, annotating the discovered service information with ontology mark-up languages, and classifying the annotated service information by means of specific service domain knowledge, taking into account the heterogeneous and context-dependent nature of Digital Ecosystem services and the heterogeneous nature of service providers. The methodology is realized by the prototype of a Semantic Crawler, the aim of which is to discover service advertisements and service provider profiles from webpages, and annotating the information with service domain ontologies.The service retrieval methodology enables service requesters to precisely retrieve the annotated service information, taking into account the heterogeneous nature of Digital Ecosystem service requesters. The methodology is presented by the prototype of a Service Search Engine. Since service requesters can be divided according to the group which has relevant knowledge with regard to their service requests, and the group which does not have relevant knowledge with regard to their service requests, we respectively provide two different service retrieval modules. The module for the first group enables service requesters to directly retrieve service information by querying its attributes. The module for the second group enables service requesters to interact with the search engine to denote their queries by means of service domain knowledge, and then retrieve service information based on the denoted queries.The service concept recommendation methodology concerns the issue of incomplete or incorrect queries. The methodology enables the search engine to recommend relevant concepts to service requesters, once they find that the service concepts eventually selected cannot be used to denote their service requests. We premise that there is some extent of overlap between the selected concepts and the concepts denoting service requests, as a result of the impact of service requesters’ understandings of service requests on the selected concepts by a series of human-computer interactions. Therefore, a semantic similarity model is designed that seeks semantically similar concepts based on selected concepts.The QoS evaluation and service ranking methodology is proposed to allow service requesters to evaluate the trustworthiness of a service advertisement and rank retrieved service advertisements based on their QoS values, taking into account the contextdependent nature of services in Digital Ecosystems. The core of this methodology is an extended CCCI (Correlation of Interaction, Correlation of Criterion, Clarity of Criterion, and Importance of Criterion) metrics, which allows a service requester to evaluate the performance of a service provider in a service transaction based on QoS evaluation criteria in a specific service domain. The evaluation result is then incorporated with the previous results to produce the eventual QoS value of the service advertisement in a service domain. Service requesters can rank service advertisements by considering their QoS values under each criterion in a service domain.The methodology for service domain knowledge updating, service-provider-based SDE metadata publishing, maintenance, and classification is initiated to allow: 1) knowledge users to update service domain ontologies employed in the service retrieval methodology, taking into account the dynamic nature of services in Digital Ecosystems; and 2) service providers to update their service profiles and manually annotate their published service advertisements by means of service domain knowledge, taking into account the dynamic nature of service providers in Digital Ecosystems. The methodology for service domain knowledge updating is realized by a voting system for any proposals for changes in service domain knowledge, and by assigning different weights to the votes of domain experts and normal users.In order to validate the customized semantic service retrieval methodology, we build a prototype – a Customized Semantic Service Search Engine. Based on the prototype, we test the mathematical algorithms involved in the methodology by a simulation approach and validate the proposed functions of the methodology by a functional testing approach

Opal: In Vivo Based Preservation Framework for Locating Lost Web Pages

We present Opal, a framework for interactively locating missing web pages (http status code 404). Opal is an example of in vivo preservation: harnessing the collective behavior of web archives, commercial search engines, and research projects for the purpose of preservation. Opal servers learn from their experiences and are able to share their knowledge with other Opal servers using the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH). Using cached copies that can be found on the web, Opal creates lexical signatures which are then used to search for similar versions of the web page. Using the OAI-PMH to facilitate inter-Opal learning extends the utilization of OAI-PMH in a novel manner. We present the architecture of the Opal framework, discuss a reference implementation of the framework, and present a quantitative analysis of the framework that indicates that Opal could be effectively deployed