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.

DemonD

2010 ◽  
pp. 652-668
Author(s):  
Charles Delalonde ◽  
Eddie Soulier
Keyword(s):  
Knowledge Management ◽  
Information Retrieval ◽  
Community Participation ◽  
Search Engine ◽  
Management Practices ◽  
Actor Network Theory ◽  
Social Search ◽  
Retrieval Systems ◽  
Knowledge Management Practices ◽  
Collaborative Information Retrieval

This research leverages information retrieval activity in order to build a network of organizational expertise in a distributed R&D laboratory. The authors describe traditional knowledge management practices and review post-cognitivists theories in order to define social creation in collaborative information retrieval activity. The Actor-Network theory accurately describes association processes and includes both human and non-human entities. This chapter compares this theory with the emergence of Social Search services online and Experts’ Retrieval Systems. The chapter authors suggest afterward, a social search engine named DemonD that identifies documents but more specifically users relevant to a query. DemonD relies on transparent profile construction based upon user activity, community participation, and shared documents. Individuals are invited to participate in a dedicated newsgroup and the information exchanged is capitalized. The evaluation of our service both ergonomic and through a simulation provides encouraging data.

Web Resources on Medical Tourism

2019 ◽  
pp. 174-195
Author(s):  
S. Naseehath
Keyword(s):  
Information Retrieval ◽  
Search Engine ◽  
Search Engines ◽  
Medical Tourism ◽  
Engine Performance ◽  
Link Analysis ◽  
Search Results ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
General Search

Webometric research has fallen into two main categories, namely link analysis and search engine evaluation. Search engines are also used to collect data for link analysis. A set of measurements is proposed for evaluating web search engine performance. Some measurements are adapted from the concepts of recall and precision, which are commonly used in evaluating traditional information retrieval systems. Others are newly developed to evaluate search engine stability, which is unique to web information retrieval systems. Overlapping of search results, annual growth of search results on each search engines, variation of results on search using synonyms are also used to evaluate the relative efficiency of search engines. In this study, the investigator attempts to conduct a webometric study on the topic medical tourism in Kerala using six search engines; these include three general search engines, namely Bing, Google, and Lycos, and three metasearch engines, namely Dogpile, ixquick, and WebCrawler.

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.

How well does Google work with Persian documents?

2016 ◽  
Vol 43 (3) ◽  
pp. 316-327 ◽  
Author(s):  
Mohammad Sadeghi ◽  
Jesús Vegas
Keyword(s):  
Information Retrieval ◽  
Search Engine ◽  
Morphological Analysis ◽  
Retrieval System ◽  
Relevant Information ◽  
Information Retrieval System ◽  
Search Results ◽  
Persian Language ◽  
Google Search ◽  
The Web

The performance evaluation of an information retrieval system is a decisive aspect of the measure of the improvements in search technology. The Google search engine, as a tool for retrieving information on the Web, is used by almost 92% of Iranian users. The purpose of this paper is to study Google’s performance in retrieving relevant information from Persian documents. The information retrieval effectiveness is based on the precision measures of the search results done to a website that we have built with the documents of a TREC standard corpus. We asked Google for 100 topics available on the corpus and we compared the retrieved webpages with the relevant documents. The obtained results indicated that the morphological analysis of the Persian language is not fully taken into account by the Google search engine. The incorrect text tokenisation, considering the stop words as the content keywords of a document and the wrong ‘variants encountered’ of words found by Google are the main reasons that affect the relevance of the Persian information retrieval on the Web for this search engine.

Research on Automatic Construction of Financial Ontology Using Chinese Encyclopedia Resource

2013 ◽  
Vol 765-767 ◽  
pp. 1240-1244
Author(s):  
Qian Mo ◽  
Shu Zhang
Keyword(s):  
Artificial Intelligence ◽  
Knowledge Management ◽  
Information Retrieval ◽  
Semantic Web ◽  
Large Scale ◽  
Semantic Information ◽  
Dominant Role ◽  
Experimental Results ◽  
Automatic Construction ◽  
Scale Creation

Ontology plays a dominant role in a growing number of different fields, such as information retrieval, artificial intelligence, semantic Web and knowledge management, etc. However, manual construction of large ontology is not feasible. This article discusses how to create Financial Ontology automatically from a resource of Chinese Encyclopedia. Financial Ontology includes Is-A relationship, Class-Instance relationship, Attribute-of relationship and Synonym relationship. Experimental Results show us that the constructed Financial Ontology has great advantages in the large scale, creation cost and the richness of semantic information.

Enhancing Information Retrieval Capabilities of Knowledge Management Systems

2012 ◽  
pp. 248-274 ◽  
Author(s):  
Dinesh Rathi ◽  
Shannon Lucky ◽  
Ali Shiri
Keyword(s):  
Knowledge Management ◽  
Information Retrieval ◽  
Service Delivery ◽  
Support Services ◽  
Organizational Context ◽  
Controlled Vocabulary ◽  
Search Results ◽  
Tag Cloud ◽  
Knowledge Repositories ◽  
Face Complex

User support services face complex problems in the efficient and satisfactory delivery of services to users. Knowledge management (KM) principles can be effectively implemented within this organizational context to support efficient and effective problem solving to improve service delivery to the users. A KM system with good information retrieval capabilities is critical in empowering front line employees to utilize organizational knowledge repositories for better service delivery. The purpose of this chapter is to present different aspects of the major information retrieval techniques that can be used in a user services environment and to propose new models to enhance retrieval capabilities of KM systems. The authors discuss the basic elements that make up an information retrieval system including metadata, controlled, and uncontrolled vocabularies. The authors also propose three experimental search interfaces for enhancing information retrieval capabilities of a KM system. The first uses a thesaurus for enhanced retrieval features through better query formulation and browsing of search results; the second uses the tag cloud concept to present thesaurus terms; and the third combines the structure of a controlled vocabulary with the flexibility of a folksonomy and tag cloud, thus incorporating the beneficial aspects of both uncontrolled and controlled vocabularies to support retrieval within a heterogeneous corporate environment.

DemonD

2010 ◽  
pp. 165-183
Author(s):  
Charles Delalonde ◽  
Eddie Soulier
Keyword(s):  
Knowledge Management ◽  
Information Retrieval ◽  
Community Participation ◽  
Search Engine ◽  
Management Practices ◽  
Actor Network Theory ◽  
Social Search ◽  
Retrieval Systems ◽  
Knowledge Management Practices ◽  
Collaborative Information Retrieval

This research leverages information retrieval activity in order to build a network of organizational expertise in a distributed R&D laboratory. The authors describe traditional knowledge management practices and review post-cognitivists theories in order to define social creation in collaborative information retrieval activity. The Actor-Network theory accurately describes association processes and includes both human and non-human entities. This chapter compares this theory with the emergence of Social Search services online and Experts’ Retrieval Systems. The chapter authors suggest afterward, a social search engine named DemonD that identifies documents but more specifically users relevant to a query. DemonD relies on transparent profile construction based upon user activity, community participation, and shared documents. Individuals are invited to participate in a dedicated newsgroup and the information exchanged is capitalized. The evaluation of our service both ergonomic and through a simulation provides encouraging data.

scholarly journals An ontology of sstronomical object types for the Virtual Observatory

2006 ◽  
Vol 2 (14) ◽  
pp. 603-603 ◽  
Author(s):  
Sebastian Derriere ◽  
André Richard ◽  
Andrea Preite-Martinez
Keyword(s):  
Knowledge Management ◽  
Semantic Web ◽  
Knowledge Base ◽  
Emerging Technologies ◽  
Software Components ◽  
Virtual Observatory ◽  
Inference Engines ◽  
Advanced Knowledge

The Semantic Web and ontologies are emerging technologies that enable advanced knowledge management and sharing. Their application to Astronomy can offer new ways of sharing information between astronomers, but also between machines or software components and allow inference engines to perform reasoning on an astronomical knowledge base. The first examples of astronomy-related ontologies are being developed in the european VOTech project.

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