scholarly journals Algorithms of relationships and dependencies search in Web-pages

2016 ◽  
pp. 044-050 ◽  
Author(s):  
A.M. Glybovets ◽  
◽  
Keyword(s):  
Information Retrieval ◽  
Computer Science ◽  
Search Engine ◽  
Data Storage ◽  
Data Selection ◽  
Web Pages ◽  
Retrieval Systems ◽  
Data Store ◽  
Information Retrieval Systems ◽  
Existing Data

Methods of extraction and analysis of data – a relatively new and promising branch of computer science, has found its application in information retrieval systems. An algorithm of relationships and dependencies searching in the collections of Web pages. The algorithm does not provide relevant search resources. This function is performed by the search engine. It also produces cleaning, integration, and data selection. A special feature of the algorithm is to use the existing data store (search engine or data storage), language independence and ease of implementation.

A User-Centered Approach for Information Retrieval

2011 ◽  
pp. 165-178 ◽  
Author(s):  
Antonio Picariello
Keyword(s):  
Information Retrieval ◽  
Relevance Feedback ◽  
Statistical Information ◽  
Web Pages ◽  
General Knowledge ◽  
Test Set ◽  
Retrieval Technique ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Relevant Component

Information retrieval can take great advantages and improvements considering users’ feedbacks. Therefore, the user dimension is a relevant component that must be taken into account while planning and implementing real information retrieval systems. In this chapter, we first describe several concepts related to relevance feedback methods, and then propose a novel information retrieval technique which uses the relevance feedback concepts in order to improve accuracy in an ontology-based system. In particular, we combine the Semantic information from a general knowledge base with statistical information using relevance feedback. Several experiments and results are presented using a test set constituted of Web pages.

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.

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.

Domain-specific readability measures to improve information retrieval in the Persian language

2018 ◽  
Vol 36 (3) ◽  
pp. 430-444
Author(s):  
Sholeh Arastoopoor
Keyword(s):  
Information Retrieval ◽  
Computer Science ◽  
Web Search ◽  
Content Type ◽  
Domain Specific ◽  
Search Results ◽  
Persian Language ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Primary Focus

Purpose The degree to which a text is considered readable depends on the capability of the reader. This assumption puts different information retrieval systems at the risk of retrieving unreadable or hard-to-be-read yet relevant documents for their users. This paper aims to examine the potential use of concept-based readability measures along with classic measures for re-ranking search results in information retrieval systems, specifically in the Persian language. Design/methodology/approach Flesch–Dayani as a classic readability measure along with document scope (DS) and document cohesion (DC) as domain-specific measures have been applied for scoring the retrieved documents from Google (181 documents) and the RICeST database (215 documents) in the field of computer science and information technology (IT). The re-ranked result has been compared with the ranking of potential users regarding their readability. Findings The results show that there is a difference among subcategories of the computer science and IT field according to their readability and understandability. This study also shows that it is possible to develop a hybrid score based on DS and DC measures and, among all four applied scores in re-ranking the documents, the re-ranked list of documents based on the DSDC score shows correlation with re-ranking of the participants in both groups. Practical implications The findings of this study would foster a new option in re-ranking search results based on their difficulty for experts and non-experts in different fields. Originality/value The findings and the two-mode re-ranking model proposed in this paper along with its primary focus on domain-specific readability in the Persian language would help Web search engines and online databases in further refining the search results in pursuit of retrieving useful texts for users with differing expertise.

What does good look like?

2019 ◽  
Vol 53 (2) ◽  
pp. 76-81
Author(s):  
Theo Huibers ◽  
Monica Landoni ◽  
Maria Soledad Pera ◽  
Jerry Alan Fails ◽  
Emiliana Murgia ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Graduate Students ◽  
Computer Science ◽  
Interaction Design ◽  
Retrieval System ◽  
Short Review ◽  
Information Retrieval System ◽  
Good Information ◽  
Retrieval Systems ◽  
Information Retrieval Systems

This short review discusses the outcomes of the 3 rd Workshop of the International and Interdisciplinary Perspectives on Children & Recommender and Information Retrieval Systems (KidRec 2019) , co-located with the 2019 ACM Interaction Design and Children (IDC) Conference, which took place June 12-15 in Boise, Idaho, USA. The goal for the workshop was to explore the characteristics of a "good" information retrieval system for children. The diversity of attendees - including industry representatives, undergraduate and graduate students, and senior scholars in various areas of computer science - made it possible to continue to build community around this important topic and further discuss and outline the salient concerns and the next steps to promote further exploration in this area.

scholarly journals Comparative Analysis of Information Retrieval using Ontology Based vs Traditional Information Systems in Food Science Domain

2020 ◽  
Vol 40 (02) ◽  
pp. 437-444
Author(s):  
Padmavathi T
Keyword(s):  
Information Retrieval ◽  
Information Systems ◽  
Retrieval System ◽  
Food Science ◽  
Web Pages ◽  
Average Precision ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Science Domain ◽  
Server Application

The current methods of searching and information retrieval are imprecise, often yielding results in tens of thousands of web pages. Extraction of the actual information needed often requires extensive manual browsing of retrieved documents. In order to address these drawbacks, this paper introduces an implementation in the field of food science of the ontology-based information retrieval system, and comparison is made with conventional information systems. The ontology of Food Semantic Web Knowledge Base (FSWKB) was built using the Protégé framework which supports two main models of ontology through the editors Protégé-Frames and Protégé-OWL. The FSWKB is composed of two heterogeneous ontologies, and these are merged and processed on a separate server application making use of the Apache Jena Fuseki an SPARQL server offering SPARQL endpoint. The experimental results indicated that ontology-based information systems are more effective in terms of their retrieval capability compared to the more conventional information retrieval systems. The retrieval effectiveness was measured in terms of precision and recall. The results of the work showed that traditional search results in average precision and recall levels of 0.92 and 0.18. The ontology-based test for precision and recall has average rates of 0.96 and 0.97.

A Study on Effective Measurement of Search Results from Search Engines

2019 ◽  
Vol 27 (1) ◽  
pp. 196-221 ◽  
Author(s):  
Jin Zhang ◽  
Xin Cai ◽  
Taowen Le ◽  
Wei Fei ◽  
Feicheng Ma
Keyword(s):  
Information Retrieval ◽  
Information Management ◽  
Search Engine ◽  
Information Search ◽  
Search Engines ◽  
Internet Technology ◽  
Global Information ◽  
Search Results ◽  
Retrieval Systems ◽  
Information Retrieval Systems

This article describes how as internet technology continues to change and improve lives and societies worldwide, effective global information management becomes increasingly critical, and effective Internet information retrieval systems become more and more significant in providing Internet users worldwide with accurate and complete information. Search engine evaluation is an important research field as search engines directly determine the quality of information users' Internet searches. Relevance-decrease pattern/model plays an important role in search engine result evaluation. This research studies effective measurement of search results through investigating relevance-decrease patterns of search results from two popular search engines: Google and Bing. The findings can be applied to relevance-evaluation of search results from other information retrieval systems such as OPAC, can help make search engine evaluations more accurate and sound, and can provide global information management personnel with valuable insights.

Incremental Refinement of Page Ranking of Web Pages

2020 ◽  
Vol 10 (3) ◽  
pp. 57-73
Author(s):  
Prem Sagar Sharma ◽  
Divakar Yadav
Keyword(s):  
Information Retrieval ◽  
Web Pages ◽  
Web Based ◽  
Query Log ◽  
Large Size ◽  
Retrieval Systems ◽  
Page Ranking ◽  
User Query ◽  
Information Retrieval Systems ◽  
Ranking Mechanism

Web-based information retrieval systems called search engines have made things easy for information seekers, but still do not provide guarantees about the relevance of the information provided to the users. Information retrieval systems provide the information to the user based on certain retrieval criteria. Due to the large size of the WWW, it is very common that a large number of documents get identified related to a particular domain. Therefore, to help users towards finding the best matching documents, a ranking mechanism is employed by the search engine. In this article, an improved architecture for an information retrieval system is proposed. The proposed system makes a query log for each user query and stores the results retrieved to the user for that query. The system also provides relevant results by analyzing the content of the pages retrieved for the user query.

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