Viewpoints in indexing term assignment

2019 ◽  
Vol 71 (4) ◽  
pp. 450-461 ◽  
Author(s):  
David Bodoff ◽  
Yaffa Richter‐Levin
Keyword(s):  
Indexing Term

LocalContent: a personal scientific document retrieval system

2015 ◽  
Vol 33 (3) ◽  
pp. 373-385 ◽  
Author(s):  
Chih-Fong Tsai ◽  
Shih-Wen Ke ◽  
Kenneth McGarry ◽  
Ming-Yi Lin
Keyword(s):  
Language Processing ◽  
Retrieval System ◽  
Personal Information ◽  
Document Retrieval ◽  
Processing Technique ◽  
Content Type ◽  
Indexing And Retrieval ◽  
Database Indexing ◽  
Personal Archives ◽  
Indexing Term

Purpose – The purpose of this paper is to introduce a novel personal scientific document retrieval system. The most common approach taken for the storage of personal documents is to construct a hierarchical folder structure. Most users prefer searching for documents by manually traversing their organizational hierarchy until reaching the location where the target item is stored, then locating the specific documents within its directory or folder. However, this is very time-consuming, especially when the number of personal scientific documents is very large. Unfortunately, related personal information management (PIM) systems, which provide solutions for managing various types of personal information, have thus far made little progress at managing personal scientific documents. Design/methodology/approach – In this paper, we introduce the design of a personal scientific document retrieval system, namely, LocalContent. It is composed of database indexing and retrieval stages. During indexing, term feature extraction from scientific documents is performed by the natural language processing technique. The extracted terms are stored in the inverted index for later retrieval. For retrieval, a graphical user interface is provided by LocalContent, which allows users to search their personal scientific documents. Findings – The evaluation results based on 20 different personal archives taken from 20 graduate students show that LocalContent is simple to use and can facilitate the search for relevant scientific documents. Moreover, these users were willing to have a system which provides specialized search functions like LocalContent to explore their personal scientific documents in the future. Originality/value – LocalContent is a novel scientific document retrieval system and provides several particular functions of LocalContent including displaying the content summary of the query term frequency in each specific section of the retrieved documents, querying by local section specification and providing a number of recommended keywords related to the query terms.

scholarly journals Content Management - Concept and Indexing Term Equivalence in a Multilingual Thesaurus

10.28945/2511 ◽  
2002 ◽  
Author(s):  
Susanna Keränen
Keyword(s):  
Information Science ◽  
Content Management ◽  
Controlled Vocabulary ◽  
Language And Culture ◽  
Term Equivalence ◽  
Data Collection And Analysis ◽  
Information Studies ◽  
Management Concept ◽  
Indexing Term

Languages and the thinking they reflect stem mainly from cultural needs for expression. A controlled vocabulary, thesaurus, can be seen as a cultural product. The focus of this study is the translatability of British-English social science indexing terms into Finnish language and culture on a conceptual, term and indexing term level. The emphasis is on Finnish language and human factors. The study is quantitative-qualitative and the perspectives are both linguistic and sociological - a combination through which a broader understanding of the phenomena is being aimed at in the general frame of information science. The study uses multiple cases aiming at theoretical replication. It is thus an empirical case study and the goal is to illustrate a new theory of “pragmatic indexing (term) equivalence”. Several data collection and analysis methods will be used in order to construct a theory by triangulation of evidence. The aim of this research is a doctoral thesis in information studies.

scholarly journals Entropy-Based Incremental Indexing Term Selection Method for N-gram Full Text Search System

2005 ◽  
Vol 125 (5) ◽  
pp. 730-731 ◽  
Author(s):  
Hiroshi Yamamoto ◽  
Ryosuke Saga ◽  
Satoru Moriyama ◽  
Hiroshi Tsuji
Keyword(s):  
Full Text ◽  
Selection Method ◽  
Text Search ◽  
Search System ◽  
Full Text Search ◽  
Term Selection ◽  
N Gram ◽  
Indexing Term
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