Technologies for Information Access and Knowledge Management

2011 ◽  
pp. 3680-3685
Author(s):  
Thomas Mandl
Keyword(s):  
Information Retrieval ◽  
Search Engines ◽  
Information Access ◽  
Partial Match ◽  
Retrieval Models ◽  
Automatic Indexing ◽  
Patent Retrieval ◽  
Information Retrieval Systems ◽  
Information Work ◽  
The 1960S

In the 1960s, automatic indexing methods for texts were developed. They had already implemented the “bag-ofwords” approach, which still prevails. Although automatic indexing is widely used today, many information providers and even Internet services still rely on human information work. In the 1970s, research shifted its interest to partial-match retrieval models and proved their superiority over Boolean retrieval models. Vector-space and later probabilistic retrieval models were developed. However, it took until the 1990s for partial-match models to succeed in the market. The Internet played a great role in this success. All Web search engines were based on partial-match models and provided ranked lists as results rather than unordered sets of documents. Consumers got used to this kind of search systems, and all big search engines included partial-match functionality. However, there are many niches in which Boolean methods still dominate, for example, patent retrieval. The basis for information retrieval systems may be pictures, graphics, videos, music objects, structured documents, or combinations thereof. This article is mainly concerned with information retrieval for text documents.

Search Variability and Interlibrary Services

Infolib ◽  
2020 ◽  
Vol 24 (4) ◽  
pp. 16-21
Author(s):  
Irina Krasilnikova ◽  
Keyword(s):  
Information Retrieval ◽  
Search Engines ◽  
Electronic Resources ◽  
Scientific Publications ◽  
Retrieval Systems ◽  
Electronic Catalogs ◽  
Information Retrieval Systems ◽  
Modern Information ◽  
Foreign Materials ◽  
Search For Information

The urgency of the problem is associated with an increase in the number of electronic resources in many information and library institutions, the need to search for information from any sources, including external ones, the provision of documents from a group of funds (corporations), the presence of electronic catalogs and search systems. Finding information from catalogs and other search engines has always preceded the execution of orders in the interlibrary service. Borrowing and using documents from different collections (provision of interlibrary services) is possible only if there is up-to-date metadata of modern information retrieval systems (ISS). The purpose of the article is to summarize the results of studying several types of search engines. At the same time, attention was drawn to new scientific publications on the topic under study. An analysis of domestic and foreign materials on the options for searching for information is presented, which is very necessary for users, including those who are remote in the provision of interlibrary services.

Service-Oriented Architectures for Context-Aware Information Retrieval and Access

2010 ◽  
pp. 1549-1560
Author(s):  
Lu Yan
Keyword(s):  
Information Retrieval ◽  
Information Exchange ◽  
Exchange Process ◽  
Information Access ◽  
Mobile Service ◽  
Context Aware ◽  
Service Oriented Architectures ◽  
Information Retrieval Systems ◽  
To Come ◽  
Process Context

Humans are quite successful at conveying ideas to each other and retrieving information from interactions appropriately. This is due to many factors: the richness of the language they share, the common understanding of how the world works, and an implicit understanding of everyday situations (Dey & Abowd, 1999). When humans talk with humans, they are able to use implicit situational information (i.e., context) to enhance the information exchange process. Context (Cool & Spink, 2002) plays a vital part in adaptive and personalized information retrieval and access. Unfortunately, computer communications lacks this ability to provide auxiliary context in addition to the substantial content of information. As computers are becoming more and more ubiquitous and mobile, there is a need and possibility to provide information “personalized, any time, and anywhere” (ITU, 2006). In these scenarios, large amounts of information circulate in order to create smart and proactive environments that will significantly enhance both the work and leisure experiences of people. Context-awareness plays an important role to enable personalized information retrieval and access according to the current situation with minimal human intervention. Although context-aware information retrieval systems have been researched for a decade (Korkea-aho, 2000), the rise of mobile and ubiquitous computing put new challenges to issue, and therefore we are motivated to come up with new solutions to achieve non-intrusive, personalized information access on the mobile service platforms and heterogeneous wireless environments.

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.

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.

Information Retrieval Models

2017 ◽  
pp. 17-42 ◽  
Author(s):  
Saruladha Krishnamurthy ◽  
Akila V
Keyword(s):  
Information Retrieval ◽  
Research Field ◽  
Process Models ◽  
Retrieval Models ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
External Sources ◽  
Active Research ◽  
Cross Lingual

Information retrieval is currently an active research field with the evolution of World wide web. The objective of this chapter is to provide an insight into the information retrieval definitions, process, models. Further how traditional information retrieval has evolved and adapted for search engines is also discussed. The information retrieval models have not only been used for search purpose it also supports cross lingual translation and retrieval tasks. This chapter also outlines the CLIR process in a brief manner. The tools which are usually used for experimental and research purpose is also discussed. This chapter is organized as Introduction to the concepts of information retrieval. Description of the information retrieval process, the information retrieval models, the role of external sources like ontologies in information retrieval systems. Finally the chapter provides an overview of CLIR and the tools used in developing IR systems is mentioned. Further the latest research directions in IR is explained.

scholarly journals Information Retrieval Models

2018 ◽  
pp. 995-1015
Author(s):  
Saruladha Krishnamurthy ◽  
Akila V
Keyword(s):  
Information Retrieval ◽  
Research Field ◽  
Process Models ◽  
Retrieval Models ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
External Sources ◽  
Active Research ◽  
Cross Lingual

Information retrieval is currently an active research field with the evolution of World wide web. The objective of this chapter is to provide an insight into the information retrieval definitions, process, models. Further how traditional information retrieval has evolved and adapted for search engines is also discussed. The information retrieval models have not only been used for search purpose it also supports cross lingual translation and retrieval tasks. This chapter also outlines the CLIR process in a brief manner. The tools which are usually used for experimental and research purpose is also discussed. This chapter is organized as Introduction to the concepts of information retrieval. Description of the information retrieval process, the information retrieval models, the role of external sources like ontologies in information retrieval systems. Finally the chapter provides an overview of CLIR and the tools used in developing IR systems is mentioned. Further the latest research directions in IR is explained.

Interactive Query Expansion with Automatically Generated Category-Specific Thesauri

2011 ◽  
pp. 103-117
Author(s):  
Fabrizio Sebastiani
Keyword(s):  
Information Retrieval ◽  
Search Engines ◽  
Information Seeking ◽  
Query Expansion ◽  
Document Collections ◽  
Web Based ◽  
Interactive Query ◽  
Retrieval Systems ◽  
Subject Specific ◽  
Information Retrieval Systems

The categorization of documents into subject-specific categories is a useful enhancement for large document collections addressed by information retrieval systems, as a user can first browse a category tree in search of the category that best matches her interests and then issue a query for more specific documents “from within the category.” This approach combines two modalities in information seeking that are most popular in Web-based search engines, i.e., category-based site browsing (as exemplified by, e.g., Yahoo™) and keyword-based document querying (as exemplified by, e.g., AltaVista™). Appropriate query expansion tools need to be provided, though, in order to allow the user to incrementally refine her query through further retrieval passes, thus allowing the system to produce a series of subsequent document rankings that hopefully converge to the user’s expected ranking. In this work we propose that automatically generated, category-specific “associative” thesauri be used for such purpose. We discuss a method for their generation and discuss how the thesaurus specific to a given category may usefully be endowed with “gateways” to the thesauri specific to its parent and children categories.

Service-Oriented Architectures for Context-Aware Information Retrieval and Access

2011 ◽  
pp. 220-231
Author(s):  
Lu Yan
Keyword(s):  
Information Retrieval ◽  
Information Exchange ◽  
Exchange Process ◽  
Information Access ◽  
Mobile Service ◽  
Context Aware ◽  
Service Oriented Architectures ◽  
Information Retrieval Systems ◽  
To Come ◽  
Process Context

Humans are quite successful at conveying ideas to each other and retrieving information from interactions appropriately. This is due to many factors: the richness of the language they share, the common understanding of how the world works, and an implicit understanding of everyday situations (Dey & Abowd, 1999). When humans talk with humans, they are able to use implicit situational information (i.e., context) to enhance the information exchange process. Context (Cool & Spink, 2002) plays a vital part in adaptive and personalized information retrieval and access. Unfortunately, computer communications lacks this ability to provide auxiliary context in addition to the substantial content of information. As computers are becoming more and more ubiquitous and mobile, there is a need and possibility to provide information “personalized, any time, and anywhere” (ITU, 2006). In these scenarios, large amounts of information circulate in order to create smart and proactive environments that will significantly enhance both the work and leisure experiences of people. Context-awareness plays an important role to enable personalized information retrieval and access according to the current situation with minimal human intervention. Although context-aware information retrieval systems have been researched for a decade (Korkea-aho, 2000), the rise of mobile and ubiquitous computing put new challenges to issue, and therefore we are motivated to come up with new solutions to achieve non-intrusive, personalized information access on the mobile service platforms and heterogeneous wireless environments.

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