scholarly journals An Art of Review on Conceptual based Information Retrieval

Webology ◽  
2021 ◽  
Vol 18 (SI02) ◽  
pp. 21-31
Author(s):  
P. Mahalakshmi ◽  
N. Sabiyath Fathima
Keyword(s):  
Information Retrieval ◽  
Keyword Search ◽  
Semantic Representation ◽  
Research Work ◽  
Semantic Search ◽  
Future Research ◽  
Conceptual Information ◽  
Retrieval Systems ◽  
User Query ◽  
Information Retrieval Systems

Basically keywords are used to index and retrieve the documents for the user query in a conventional information retrieval systems. When more than one keywords are used for defining the single concept in the documents and in the queries, inaccurate and incomplete results were produced by keyword based retrieval systems. Additionally, manual interventions are required for determining the relationship between the related keywords in terms of semantics to produce the accurate results which have paved the way for semantic search. Various research work has been carried out on concept based information retrieval to tackle the difficulties that are caused by the conventional keyword search and the semantic search systems. This paper aims at elucidating various representation of text that is responsible for retrieving relevant search results, approaches along with the evaluation that are carried out in conceptual information retrieval, the challenges faced by the existing research to expatiate requirements of future research. In addition, the conceptual information that are extracted from the different sources for utilizing the semantic representation by the existing systems have been discussed.

scholarly journals A semantic search approach for hyper relational knowledge graphs

2021 ◽  
Author(s):  
Veronica dos Santos ◽  
Sérgio Lifschitz
Keyword(s):  
Information Retrieval ◽  
Semantic Search ◽  
Similarity Function ◽  
Search Results ◽  
Relational Knowledge ◽  
Retrieval Systems ◽  
User Query ◽  
Information Retrieval Systems ◽  
Knowledge Graphs ◽  
Search Approach

Information Retrieval Systems usually employ syntactic search techniques to match a set of keywords with the indexed content to retrieve results. But pure keyword-based matching lacks on capturing user's search intention and context and suffers of natural language ambiguity and vocabulary mismatch. Considering this scenario, the hypothesis raised is that the use of embeddings in a semantic search approach will make search results more meaningfully. Embeddings allow to minimize problems arising from terminology and context mismatch. This work proposes a semantic similarity function to support semantic search based on hyper relational knowledge graphs. This function uses embeddings in order to find the most similar nodes that satisfy a user query.

scholarly journals Keyword Search over the COVID-19 Data

2020 ◽  
Author(s):  
Yenier Torres Izquierdo ◽  
Grettel Monteagudo Garcia ◽  
Melissa Lemos ◽  
Alexandre Novello ◽  
Bruno Novelli ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Relational Databases ◽  
Keyword Search ◽  
Attractive Alternative ◽  
Knowledge Retrieval ◽  
Database Access ◽  
Retrieval Systems ◽  
Information Retrieval Systems

Keyword search is typically associated with information retrieval systems. However, recently, keyword search has been expanded to relational databases and RDF datasets, as an attractive alternative to traditional database access. With this motivation, this paper first introduces a platform for data and knowledge retrieval, called DANKE, concentrating on the keyword search component. It then describes an application that uses DANKE to implement keyword search over two COVID-19 data scenarios.

scholarly journals A Novel Information retrieval system for distributed cloud using Hybrid Deep Fuzzy Hashing Algorithm

2020 ◽  
Vol 02 (03) ◽  
pp. 151-160 ◽  
Author(s):  
Dr. V. Suma
Keyword(s):  
Neural Network ◽  
Information Retrieval ◽  
Deep Neural Network ◽  
Research Work ◽  
Support Vector ◽  
Retrieval Performance ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Hashing Algorithm ◽  
Distributed Cloud

The recent technology development fascinates the people towards information and its services. Managing the personal and pubic data is a perennial research topic among researchers. In particular retrieval of information gains more attention as it is important similar to data storing. Clustering based, similarity based, graph based information retrieval systems are evolved to reduce the issues in conventional information retrieval systems. Learning based information retrieval is the present trend and in particular deep neural network is widely adopted due to its retrieval performance. However, the similarity between the information has uncertainties due to its measuring procedures. Considering these issues also to improve the retrieval performance, a hybrid deep fuzzy hashing algorithm is introduced in this research work. Hashing efficiently retrieves the information based on mapping the similar information as correlated binary codes and this underlying information is trained using deep neural network and fuzzy logic to retrieve the necessary information from distributed cloud. Experimental results prove that the proposed model attains better retrieval accuracy and accuracy compared to conventional models such as support vector machine and deep neural network.

The Three Faces of Synthesis: Bringing Together Quantitative Findings in the Field of Transport and Environmental Policy

1998 ◽  
Vol 16 (5) ◽  
pp. 517-528 ◽  
Author(s):  
K J Button
Keyword(s):  
Information Retrieval ◽  
Environmental Policy ◽  
Research Work ◽  
Easy Access ◽  
Body Of Knowledge ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Modern Information ◽  
Fruitful Research ◽  
Work Done

Good policymaking is based on sound information. Seldom, however, does any research work generate findings that are genuinely new. Much research draws upon and extends bodies of existing knowledge to gain better insights or to refine the accuracy of key parameters. Modern information-retrieval systems allow increasingly easy access to the findings of previous work. One of the bigger challenges today is to keep abreast of what is actually going on, and to extract insights from the existing body of knowledge where gaps still exist and the most fruitful research may be conducted. There are three broad approaches towards our existing body of knowledge, and the aim of this paper is to examine the usefulness of these alternatives and to pinpoint the types of circumstance where one may prove more helpful than the others. It places particular attention on work done which relates to the effects that transport has on the environment.

scholarly journals Study of Query Expansion Techniques and Their Application in the Biomedical Information Retrieval

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
A. R. Rivas ◽  
E. L. Iglesias ◽  
L. Borrajo
Keyword(s):  
Information Retrieval ◽  
Query Expansion ◽  
Relevant Information ◽  
Textual Information ◽  
Retrieval Systems ◽  
Biomedical Information Retrieval ◽  
User Query ◽  
Information Retrieval Systems ◽  
Document Collection ◽  
Text Preprocessing

Information Retrieval focuses on finding documents whose content matches with a user query from a large document collection. As formulating well-designed queries is difficult for most users, it is necessary to use query expansion to retrieve relevant information. Query expansion techniques are widely applied for improving the efficiency of the textual information retrieval systems. These techniques help to overcome vocabulary mismatch issues by expanding the original query with additional relevant terms and reweighting the terms in the expanded query. In this paper, different text preprocessing and query expansion approaches are combined to improve the documents initially retrieved by a query in a scientific documental database. A corpus belonging to MEDLINE, called Cystic Fibrosis, is used as a knowledge source. Experimental results show that the proposed combinations of techniques greatly enhance the efficiency obtained by traditional queries.

scholarly journals Keyword Search over RDF Using Document-Centric Information Retrieval Systems

2020 ◽  
pp. 121-137
Author(s):  
Giorgos Kadilierakis ◽  
Pavlos Fafalios ◽  
Panagiotis Papadakos ◽  
Yannis Tzitzikas
Keyword(s):  
Information Retrieval ◽  
Keyword Search ◽  
Retrieval Systems ◽  
Information Retrieval Systems

An Overview of Video Information Retrieval Techniques

2011 ◽  
pp. 283-292
Author(s):  
Sagarmay Deb ◽  
Yanchun Zhang
Keyword(s):  
Feature Extraction ◽  
Information Retrieval ◽  
Research Work ◽  
Multimedia Databases ◽  
Video Information ◽  
The Past ◽  
Retrieval Systems ◽  
Indexing And Retrieval ◽  
Information Retrieval Systems ◽  
Efficient Video

Video information retrieval is currently a very important topic of research in the area of multimedia databases. Plenty of research work has been undertaken in the past decade to design efficient video information retrieval techniques from the video or multimedia databases. Although a large number of indexing and retrieval techniques have been developed, there are still no universally accepted feature extraction, indexing, and retrieval techniques available. In this chapter, we present an up-to-date overview of various video information retrieval systems. Since the volume of literature available in the field is enormous, only selected works are mentioned.

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.

scholarly journals A New User Model based Interactive Product Retrieval Process for improved eBuying

2015 ◽  
Vol 19 ◽  
Author(s):  
Oshadi Alahakoon
Keyword(s):  
Information Retrieval ◽  
Recommender Systems ◽  
User Model ◽  
User Preferences ◽  
Retrieval Algorithm ◽  
Retrieval Process ◽  
Retrieval Systems ◽  
User Query ◽  
Information Retrieval Systems ◽  
Interactive Product

When searching for items online there are three common problems that e-buyers may encounter; null retrieval, retrieving unmanageable number of items, and retrieving unsatisfactory items. In the past information retrieval systems or recommender systems were used as solutions. With information retrieval systems, too rigorous filtering based on the user query to reduce unmanageable number of items result in either null retrieval or filtering out the items users prefer. Recommender systems on the other hand do not provide sufficient opportunity for users to communicate their needs. As a solution, this paper introduces a novel method combining a user model with an interactive product retrieval process. The new layered user model has the potential of being applied across multiple product and service domains and is able to adapt to changing user preferences. The new product retrieval algorithm is integrated with the user model and is able to successfully address null retrieval, retrieving unmanageable number of items, and retrieving unsatisfactory items. The process is demonstrated using a bench mark dataset and a case study. Finally the Product retrieval process is evaluated using a set of guidelines to illustrate its suitability to current eBuying environments.

scholarly journals CONCEPT OF INFORMATION-SEARCH SYSTEM (ON THE BASIS OF ONTOLOGIES) FOR THE DOMAIN OF MEDICAL LAW

2020 ◽  
Vol 2 (2) ◽  
pp. 6-9
Author(s):  
T. HOVORUSHCHENKO ◽  
◽  
Y. HNATCHUK ◽  
O. SAVCHUK ◽  
◽  
...  
Keyword(s):  
Information Retrieval ◽  
Information Search ◽  
Retrieval System ◽  
Semantic Analysis ◽  
Information Retrieval System ◽  
Information Resources ◽  
Semantic Search ◽  
Medical Law ◽  
Retrieval Systems ◽  
Information Retrieval Systems

The search for information is one of the main components of human activity. The ideal information retrieval system should issue only documents that are relevant to the request. Today, real information retrieval systems provide a completeness factor of 70%, and a search accuracy factor – at a level sometimes even 10%. Thus, the well-known information retrieval systems are currently unable to meet the modern needs of users. The global trend in the processing of large arrays of information, which allows you to solve new classes of problems based on available information resources, is the intellectualization of information and data processing. As a standard of knowledge engineering in the development of information retrieval systems, it is worthwhile to use ontologies that are widely used in the work of search engines and information retrieval systems, as ontologies are an effective tool for organizing a semantic search. The use of ontologies as part of information retrieval systems helps to solve a number of methodological and technological problems that arise during the development of such systems. An important and actual task now is to develop an effective information retrieval system for the field of medical law. The purpose of this study is to develop the concept of an effective information retrieval system (based on ontologies) for the field of medical law. The paper proposes the concept of an information retrieval system (based on ontologies) for the field of medical law, which consists of: an internal ontology of semantic search, which will contain knowledge about the basic elements of the search process; taxonomies of information objects, information about which the user is looking for (this taxonomy will integrate existing ontologies of multimedia information resources, Web-services, and organizational structures); ontologies of the subject area, which will be used for the accumulation of knowledge, as well as for the construction of thesauri, dictionaries, taxonomies; linguistic ontologies designed for semantic analysis of natural information resources.

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