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 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.

An Information Retrieval System Based on Portable Device

2013 ◽  
Vol 712-715 ◽  
pp. 2706-2711
Author(s):  
Xiao Qing Yu ◽  
Wen Gen Wang ◽  
Jian Hua Shi ◽  
Yun Hui Wang
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Relevant Information ◽  
Information Retrieval System ◽  
Text Indexing ◽  
Traditional System ◽  
Related Information ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Audio Information

Information retrieval is the activity to organize information in a certain way, and according to the users demand to find out the related information from a collection of resources. Retrieval process and technology can be based on metadata or full-text indexing. Most of the relevant information retrieval systems are devised on the computer. However, with the highly development of the embedded technology, some popular application have been developed on the platform. In this paper, we will introduce an information retrieval system on the iOS platform which is more convenient, practical, and effective compared with the traditional system. And we will introduce an application based on this system design. The experiments shown that this system was exactly effective utilized to retrieval audio information.

Discovering Ranking Functions for Information Retrieval

2011 ◽  
pp. 377-381
Author(s):  
Weiguo Fan ◽  
Praveen Pathak
Keyword(s):  
Information Retrieval ◽  
World Wide ◽  
Adaptive Algorithms ◽  
Relevant Information ◽  
Ranking Function ◽  
Ranking Functions ◽  
Document Collections ◽  
Retrieval Systems ◽  
The World ◽  
Document Collection

The field of information retrieval deals with finding relevant documents from a large document collection or the World Wide Web in response to a user’s query seeking relevant information. Ranking functions play a very important role in the retrieval performance of such retrieval systems and search engines. A single ranking function does not perform well across different user queries, and document collections. Hence it is necessary to “discover” a ranking function for a particular context. Adaptive algorithms like genetic programming (GP) are well suited for such discovery.

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.

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 Arabic Query Expansion Using WordNet and Association Rules

2018 ◽  
pp. 1239-1254 ◽  
Author(s):  
Ahmed Abbache ◽  
Farid Meziane ◽  
Ghalem Belalem ◽  
Fatma Zohra Belkredim
Keyword(s):  
Information Retrieval ◽  
Association Rules ◽  
Query Expansion ◽  
Arabic Language ◽  
Selection Method ◽  
Empirical Results ◽  
Retrieval Systems ◽  
Information Retrieval Systems ◽  
Significant Performance ◽  
Selection Of

Query expansion is the process of adding additional relevant terms to the original queries to improve the performance of information retrieval systems. However, previous studies showed that automatic query expansion using WordNet do not lead to an improvement in the performance. One of the main challenges of query expansion is the selection of appropriate terms. In this paper, the authors review this problem using Arabic WordNet and Association Rules within the context of Arabic Language. The results obtained confirmed that with an appropriate selection method, the authors are able to exploit Arabic WordNet to improve the retrieval performance. Their empirical results on a sub-corpus from the Xinhua collection showed that their automatic selection method has achieved a significant performance improvement in terms of MAP and recall and a better precision with the first top retrieved documents.

Enhanced Information Retrieval Evaluation between Pseudo Relevance Feedback and Query Similarity Relevant Documents Methology Applied on Arabic Text

2009 ◽  
pp. 56-66
Author(s):  
Sameh Ghwanmeh ◽  
Ghassan Kannan ◽  
Riyad Al-Shalabi
Keyword(s):  
Information Retrieval ◽  
Query Expansion ◽  
Expansion Method ◽  
Information Need ◽  
Feedback Information ◽  
Retrieval Systems ◽  
Search Processes ◽  
Information Retrieval Systems ◽  
Information Retrieval Methods ◽  
Global Query

Information retrieval systems utilize user feedback for generating optimal queries with respect to a particular information need. However, the methods that have been developed in IR for generating these queries do not memorize information gathered from previous search processes, and hence cannot use such information in new search processes. Thus, a new search process cannot profit from the results of the previous processes. Web Information Retrieval systems should be able to maintain results from previous search processes, thus learning from previous queries and improving overall retrieval quality. In this chapter, we are using the similarity of a new query to previously learned queries. We then expand the new query by extracting terms from documents, which have been judged as relevant to these previously learned queries. Thus, the new method uses global feedback information for query expansion in contrast to local feedback information, which has been widely used in previous work in query expansion methods. Experimentally, we compared a new query expansion method with two conventional information retrieval methods in local and global query expansion to enhance the traditional information system. From the results gathered it can be concluded that although the traditional IR system performance is high, but we notice that PRF method increases the average recall and decreases the fallout measure.

Efektivitas Sistem Temu Kembali Informasi Perpustakaan Digital Institut Seni Indonesia (ISI) Yogyakarta dalam Tinjauan Recall dan Precision

2021 ◽  
Vol 28 (1) ◽  
pp. 37-48
Author(s):  
Thoriq Tri Prabowo
Keyword(s):  
Information Retrieval ◽  
Interior Design ◽  
Digital Library ◽  
Digital Libraries ◽  
Retrieval System ◽  
Relevant Information ◽  
Information Retrieval System ◽  
Digital Information ◽  
Retrieval Systems ◽  
Information Retrieval Systems

Today's digital library is a necessity. A system that provides all-digital information and services requires that all aspects of it should be accessed effectively. In the context of information retrieval in digital libraries, the information retrieval systems are important instruments. The system becomes a link between relevant information and its users. Evaluation of the information retrieval system to determine its effectiveness is important to ensure that users receive good retrieval services. Recall and precision are approaches to measure the effectiveness of information retrieval systems that are widely used. This study aims to determine the effectiveness of the ISI Yogyakarta digital library retrieval system based on recall and precision approaches. This study will provide benefits for librarians in knowing the effectiveness of the information retrieval system and the extent of their accuracy in indexing. This research uses an experimental method with a quantitative approach. The researcher chose a sample of the searching keywords purposively and then tested them by searching on the portal http://digilib.isi.ac.id/. The data obtained were analyzed using the formula recall and precision. In this study the subjects tested were interior design subjects. The precision measurement of 10 keywords on the subject of interior design gets 92.37% results while the recall measurement gets 80.79% results. The result stated that precision is higher than recall, it showed that the information retrieval system of ISI Yogyakarta’s digital library is quite effective.

Sign in / Sign up

Export Citation Format

Share Document