An Associative and Adaptive Network Model For Information Retrieval In The Semantic Web

2010 ◽  
pp. 309-344
Author(s):  
Peter Scheir ◽  
Peter Prettenhofer ◽  
Stefanie N. Lindstaedt ◽  
Chiara Ghidini
Keyword(s):  
Information Retrieval ◽  
Semantic Web ◽  
Soft Computing ◽  
Relevance Feedback ◽  
Semantic Information ◽  
Retrieval Performance ◽  
Search Results ◽  
Low Coverage ◽  
Relevant Material ◽  
The Web

While it is agreed that semantic enrichment of resources would lead to better search results, at present the low coverage of resources on the web with semantic information presents a major hurdle in realizing the vision of search on the Semantic Web. To address this problem, this chapter investigates how to improve retrieval performance in settings where resources are sparsely annotated with semantic information. Techniques from soft computing are employed to find relevant material that was not originally annotated with the concepts used in a query. The authors present an associative retrieval model for the Semantic Web and evaluate if and to which extent the use of associative retrieval techniques increases retrieval performance. In addition, the authors present recent work on adapting the network structure based on relevance feedback by the user to further improve retrieval effectiveness. The evaluation of new retrieval paradigms - such as retrieval based on technology for the Semantic Web - presents an additional challenge since no off-the-shelf test corpora exist. Hence, this chapter gives a detailed description of the approach taken to evaluate the information retrieval service the authors have built.

A Roadmap to Integrate Document Clustering in Information Retrieval

2013 ◽  
pp. 31-45
Author(s):  
R. Subhashini ◽  
V.Jawahar Senthil Kumar
Keyword(s):  
Information Retrieval ◽  
Search Engines ◽  
World Wide ◽  
Clustering Algorithm ◽  
Web Search ◽  
Full Potential ◽  
Digital Information ◽  
Search Results ◽  
The World ◽  
The Web

The World Wide Web is a large distributed digital information space. The ability to search and retrieve information from the Web efficiently and effectively is an enabling technology for realizing its full potential. Information Retrieval (IR) plays an important role in search engines. Today’s most advanced engines use the keyword-based (“bag of words”) paradigm, which has inherent disadvantages. Organizing web search results into clusters facilitates the user’s quick browsing of search results. Traditional clustering techniques are inadequate because they do not generate clusters with highly readable names. This paper proposes an approach for web search results in clustering based on a phrase based clustering algorithm. It is an alternative to a single ordered result of search engines. This approach presents a list of clusters to the user. Experimental results verify the method’s feasibility and effectiveness.

Using Semantic Web Concepts to Retrieve Specific Domain Information from the Web

2011 ◽  
pp. 249-270
Author(s):  
Rafael Cunha Cardoso ◽  
Fernando da Fonseca de Souza ◽  
Ana Carolina Salgado
Keyword(s):  
Information Retrieval ◽  
World Wide Web ◽  
Semantic Web ◽  
Web Sites ◽  
World Wide ◽  
Specific Domain ◽  
New Concepts ◽  
The World ◽  
Domain Information ◽  
The Web

Currently, systems dedicated to information retrieval/extraction perform an important role on fetching relevant and qualified information from the World Wide Web (WWW). The Semantic Web can be described as the Web’s future once it introduces a set of new concepts and tools. For instance, ontology is used to insert knowledge into contents of the current WWW to give meaning to such contents. This allows software agents to better understand the Web’s content meaning so that such agents can execute more complex and useful tasks to users. This work introduces an architecture that uses some Semantic Web concepts allied to Regular Expressions (REGEX) in order to develop a system that retrieves/extracts specific domain information from the Web. A prototype, based on such architecture, was developed to find information about offers announced on supermarkets Web sites.

User Models for Adaptive Information Retrieval on the Web

2012 ◽  
Vol 3 (3) ◽  
pp. 1-19
Author(s):  
Max Chevalier ◽  
Christine Julien ◽  
Chantal Soulé-Dupuy
Keyword(s):  
Information Retrieval ◽  
Search Engines ◽  
User Profile ◽  
User Model ◽  
User Models ◽  
Search Results ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Adaptive Information Retrieval ◽  
The Web

Searching information can be realized thanks to specific tools called Information Retrieval Systems IRS (also called “search engines”). To provide more accurate results to users, most of such systems offer personalization features. To do this, each system models a user in order to adapt search results that will be displayed. In a multi-application context (e.g., when using several search engines for a unique query), personalization techniques can be considered as limited because the user model (also called profile) is incomplete since it does not exploit actions/queries coming from other search engines. So, sharing user models between several search engines is a challenge in order to provide more efficient personalization techniques. A semantic architecture for user profile interoperability is proposed to reach this goal. This architecture is also important because it can be used in many other contexts to share various resources models, for instance a document model, between applications. It is also ensuring the possibility for every system to keep its own representation of each resource while providing a solution to easily share it.

Search Engine

2011 ◽  
pp. 74-100
Author(s):  
Eliana Campi ◽  
Gianluca Lorenzo
Keyword(s):  
Knowledge Management ◽  
Information Retrieval ◽  
Semantic Web ◽  
Knowledge Base ◽  
Search Engine ◽  
Automatic Classification ◽  
Efficient Approach ◽  
Search Results ◽  
The Creation ◽  
F Measure

This chapter presents technologies and approaches for information retrieval in a knowledge base. We intend to show that the use of ontology for domain representation and knowledge search offers a more efficient approach for knowledge management. This approach focuses on the meaning of the word, thus becoming an important element in the building of the Semantic Web. The search based on both keywords and ontology allows more effective information retrieval exploiting the Semantic of the information in a variety of data. We present a method for taxonomy building, annotating, and searching documents with taxonomy concepts. We also describe our experience in the creation of an informal taxonomy, the automatic classification, and the validation of search results with traditional measures, such as precision, recall and f-measure.

Relation-Based Information Retrieval

2005 ◽  
Vol 04 (02) ◽  
pp. 133-138
Author(s):  
D. Manjula ◽  
T. V. Geetha
Keyword(s):  
Information Retrieval ◽  
Semantic Information ◽  
Irrelevant Information ◽  
Semantic Relations ◽  
Retrieval Performance ◽  
Additional Dimension ◽  
Word Context ◽  
Semantic Dimension ◽  
Word Senses ◽  
Insight Into

The traditional Boolean word-based approach to information retrieval (IR) considers only words for indexing. Irrelevant information is retrieved because of non-inclusion of semantic information like word senses and word context. In this work, the importance of representing the documents along another semantic dimension in addition to sense context information is considered. The incorporation of semantic relations as an additional dimension gives a better insight into the interpretation of the document. The micro-contexts generated from the documents are also used in indexing. The retrieval performance is measured in terms of precision and recall. The results tabulated show better performance.

WEBYACHT: A CONCEPT-BASED SEARCH TOOL FOR WWW

1999 ◽  
Vol 08 (02) ◽  
pp. 137-156 ◽  
Author(s):  
CHING-CHI HSU ◽  
CHIA-HUI CHANG
Keyword(s):  
Information Search ◽  
Relevance Feedback ◽  
Web Search ◽  
Automatic Assessment ◽  
Feedback Mechanisms ◽  
Document Ranking ◽  
Search Results ◽  
Web Information ◽  
Search Tool ◽  
The Web

This paper describes a Web information search tool called WebYacht. The goal of WebYacht is to solve the problem of imprecise search results in current Web search engines. Due to incomplete information given by users and the diversified information published on the Web, conventional document ranking based on an automatic assessment of document relevance to the query may not be the best approach when little information is given as in most cases. In order to clarify the ambiguity of the short queries given by users, WebYacht adopts cluster-based browsing model as well as relevance feedback to facilitate Web information search. The idea is to have users give two to three times more feedback in the same amount of time that would be required to give feedback for conventional feedback mechanisms. With the assistance of cluster-based representation provided by WebYacht, a lot of browsing labor can be reduced. In this paper, we explain the techniques used in the design of WebYacht and compare the performances of feedback interface designs and to conventional similarity ranking search results.

scholarly journals Analytical review on information retrieval methods and applications in the Semantic Web

2016 ◽  
pp. 051-072
Author(s):  
I.J. Grishanova ◽  
Keyword(s):  
Information Retrieval ◽  
Semantic Web ◽  
Search Engines ◽  
Search Model ◽  
Architectural Features ◽  
Proposed Model ◽  
Analytical Review ◽  
Information Retrieval Methods ◽  
The Web

The article describes and analyzes the Information Retrieval (IR) methods and applications in the environment of Semantic Web. The author provided the basic Information Retrieval concepts, problems, models and classification of IR systems on various grounds. Examples of existing modern search engines, as well as highlighted the stages of development and listed a list of functional and architectural features of 3-rd search engines generation. The proposed model of IR extends the classification of search engines and search model with the possibility of finding new objects that have become available in the web, and use knowledge represented in the Semantic Web.

scholarly journals O dispositivo como unidade básica do conhecimento na web semântica | The dispositif as the basic unit of knowledge in semantic web

2018 ◽  
Vol 14 (2) ◽  
Author(s):  
Rodrigo De Santis
Keyword(s):  
Information Retrieval ◽  
Semantic Web ◽  
Knowledge Organization ◽  
Basic Unit ◽  
Knowledge Organization System ◽  
Data Volume ◽  
Informational Environment ◽  
Historical Origins ◽  
The Web ◽  
Representation Of Knowledge

RESUMO As bases teóricas que sustentam a proposta de elaboração de um sistema de organização do conhecimento capaz de superar as limitações da abordagem dicotômica tradicional podem ser simbolizadas com o deslocamento da representação imagética do conhecimento da árvore para o rizoma. Neste contexto, o presente artigo propõe a adoção da noção filosófica de dispositivo como unidade básica do conhecimento em sistemas orientados pela recuperação. Para tanto, são investigadas as origens históricas desse deslocamento e analisados os seus impactos na web – um ambiente informacional que se torna maior a cada instante, em termos de volume de dados, e mais complexo, no que diz respeito à dispersão e à fragmentação da informação. São discutidos ainda os desafios e possíveis desdobramentos relativos à organização do conhecimento e à recuperação da informação no âmbito da web semântica.Palavras-chave: Sistema de Organização do Conhecimento; Classificação; Recuperação; Conceito.ABSTRACT The theoretical framework that supports the intent of elaborating a knowledge organization system capable of overcoming the limitations of traditional dichotomous approach can be symbolized by the displacement of the visual representation of knowledge from the tree to the rhizome. In this context, the present work proposes the adoption of the philosophical notion of dispositif as the basic unit of knowledge in systems oriented by the retrieval. To achieve this, the historical origins of that displacement were studied and its impacts on the web – an informational environment that becomes larger at each moment, in terms of data volume, and more complex, in terms of dispersion and fragmentation of information – were studied. The work also discusses the challenges and possible developments regarding knowledge organization and information retrieval in the scope of the semantic web.Keywords: Knowledge Organization System; Classification; Recovery; Concept.

User Relevance Feedback in Semantic Information Retrieval

2009 ◽  
pp. 270-281
Author(s):  
Antonio Picariello ◽  
Antonio M. Rinaldi
Keyword(s):  
Information Retrieval ◽  
Relevance Feedback ◽  
Semantic Information ◽  
Information Retrieval System ◽  
Web Pages ◽  
General Knowledge ◽  
Retrieval Systems ◽  
Crucial Component ◽  
Information Retrieval Systems ◽  
Semantic Information Retrieval

The user dimension is a crucial component in the information retrieval process and for this reason it must be taken into account in planning and technique implementation in information retrieval systems. In this paper we present a technique based on relevance feedback to improve the accuracy in an ontology based information retrieval system. Our proposed method combines the semantic information in a general knowledge base with statistical information using relevance feedback. Several experiments and results are presented using a test set constituted of Web pages.

Human-Centred Web Search

2012 ◽  
pp. 217-238 ◽  
Author(s):  
Orland Hoeber
Keyword(s):  
Information Retrieval ◽  
Decision Support ◽  
Search Engine ◽  
Information Needs ◽  
Web Search ◽  
Active Role ◽  
Simple Fact ◽  
Search Results ◽  
Retrieval Engine ◽  
The Web

People commonly experience difficulties when searching the Web, arising from an incomplete knowledge regarding their information needs, an inability to formulate accurate queries, and a low tolerance for considering the relevance of the search results. While simple and easy to use interfaces have made Web search universally accessible, they provide little assistance for people to overcome the difficulties they experience when their information needs are more complex than simple fact-verification. In human-centred Web search, the purpose of the search engine expands from a simple information retrieval engine to a decision support system. People are empowered to take an active role in the search process, with the search engine supporting them in developing a deeper understanding of their information needs, assisting them in crafting and refining their queries, and aiding them in evaluating and exploring the search results. In this chapter, recent research in this domain is outlined and discussed.

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