scholarly journals Redefining Absent Keyphrases and their Effect on Retrieval Effectiveness

Author(s):  
Florian Boudin ◽  
Ygor Gallina
2007 ◽  
Vol 41 (1) ◽  
pp. 40-57 ◽  
Author(s):  
Mounia Lalmas ◽  
Anastasios Tombros

2011 ◽  
Vol 51 (4) ◽  
pp. 732-744 ◽  
Author(s):  
Nicole Lang Beebe ◽  
Jan Guynes Clark ◽  
Glenn B. Dietrich ◽  
Myung S. Ko ◽  
Daijin Ko

2017 ◽  
Vol 73 (3) ◽  
pp. 509-527 ◽  
Author(s):  
Christiane Behnert ◽  
Dirk Lewandowski

Purpose The purpose of this paper is to demonstrate how to apply traditional information retrieval (IR) evaluation methods based on standards from the Text REtrieval Conference and web search evaluation to all types of modern library information systems (LISs) including online public access catalogues, discovery systems, and digital libraries that provide web search features to gather information from heterogeneous sources. Design/methodology/approach The authors apply conventional procedures from IR evaluation to the LIS context considering the specific characteristics of modern library materials. Findings The authors introduce a framework consisting of five parts: search queries, search results, assessors, testing, and data analysis. The authors show how to deal with comparability problems resulting from diverse document types, e.g., electronic articles vs printed monographs and what issues need to be considered for retrieval tests in the library context. Practical implications The framework can be used as a guideline for conducting retrieval effectiveness studies in the library context. Originality/value Although a considerable amount of research has been done on IR evaluation, and standards for conducting retrieval effectiveness studies do exist, to the authors’ knowledge this is the first attempt to provide a systematic framework for evaluating the retrieval effectiveness of twenty-first-century LISs. The authors demonstrate which issues must be considered and what decisions must be made by researchers prior to a retrieval test.


2013 ◽  
Vol 33 (1) ◽  
pp. 53-59 ◽  
Author(s):  
Dirk Lewandowski ◽  
Sebastian Sünkler

2019 ◽  
Vol 37 (1) ◽  
pp. 173-184 ◽  
Author(s):  
Aabid Hussain ◽  
Sumeer Gul ◽  
Tariq Ahmad Shah ◽  
Sheikh Shueb

Purpose The purpose of this study is to explore the retrieval effectiveness of three image search engines (ISE) – Google Images, Yahoo Image Search and Picsearch in terms of their image retrieval capability. It is an effort to carry out a Cranfield experiment to know how efficient the commercial giants in the image search are and how efficient an image specific search engine is. Design/methodology/approach The keyword search feature of three ISEs – Google images, Yahoo Image Search and Picsearch – was exploited to make search with keyword captions of photos as query terms. Selected top ten images were used to act as a testbed for the study, as images were searched in accordance with features of the test bed. Features to be looked for included size (1200 × 800), format of images (JPEG/JPG) and the rank of the original image retrieved by ISEs under study. To gauge the overall retrieval effectiveness in terms of set standards, only first 50 result hits were checked. Retrieval efficiency of select ISEs were examined with respect to their precision and relative recall. Findings Yahoo Image Search outscores Google Images and Picsearch both in terms of precision and relative recall. Regarding other criteria – image size, image format and image rank in search results, Google Images is ahead of others. Research limitations/implications The study only takes into consideration basic image search feature, i.e. text-based search. Practical implications The study implies that image search engines should focus on relevant descriptions. The study evaluated text-based image retrieval facilities and thereby offers a choice to users to select best among the available ISEs for their use. Originality/value The study provides an insight into the effectiveness of the three ISEs. The study is one of the few studies to gauge retrieval effectiveness of ISEs. Study also produced key findings that are important for all ISE users and researchers and the Web image search industry. Findings of the study will also prove useful for search engine companies to improve their services.


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