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Reports a laboratory comparison of the effectiveness and efficiency of five index languages in the subject area of library and information science; three post‐co‐ordinate languages, Compressed Term, Uncontrolled, and Hierarchically Structured, and two pre‐co‐ordinate ones, Hierarchically Structured and Relational Indexing. Eight test comparisons were made, and factors studied were index language specificity and linkage, indexing specificity and exhaustivity, method of co‐ordination, the precision devices of partitioning and relational operators, and the provision of context in the search file. Full details of the test and retrieval results are presented.

The purpose of this study is to assess the retrieval performance of three search engines, i.e. Google, Yahoo and Bing for navigational queries using two important retrieval measures, i.e. precision and relative recall in the field of life science and biomedicine.

Top three search engines namely Google, Yahoo and Bing were selected on the basis of their ranking as per Alexa, an analytical tool that provides ranking of global websites. Furthermore, the scope of study was confined to those search engines having interface in English. Clarivate Analytics' Web of Science was used for the extraction of navigational queries in the field of life science and biomedicine. Navigational queries (classified as one-word, two-word and three-word queries) were extracted from the keywords of the papers representing the top 100 contributing authors in the select field. Keywords were also checked for the duplication. Two important evaluation parameters, i.e. precision and relative recall were used to calculate the performance of search engines on the navigational queries.

The mean precision for Google scores high (2.30) followed by Yahoo (2.29) and Bing (1.68), while mean relative recall also scores high for Google (0.36) followed by Yahoo (0.33) and Bing (0.31) respectively.

The study is of great help to the researchers and academia in determining the retrieval efficiency of Google, Yahoo and Bing in terms of navigational query execution in the field of life science and biomedicine. The study can help users to focus on various search processes and the query structuring and its execution across the select search engines for achieving desired result list in a professional search environment. The study can also act as a ready reference source for exploring navigational queries and how these queries can be managed in the context of information retrieval process. It will also help to showcase the retrieval efficiency of various search engines on the basis of subject diversity (life science and biomedicine) highlighting the same in terms of query intention.

Though many studies have been conducted highlighting the retrieval efficiency of search engines the current work is the first of its kind to study the retrieval effectiveness of Google, Yahoo and Bing on navigational queries in the field of life science and biomedicine. The study will help in understanding various methods and approaches to be adopted by the users for the navigational query execution across a professional search environment, i.e. “life science and biomedicine”

The technical and economic feasibility of providing selective notifications of current books to specialised libraries by extraction from MARC tapes has been explored. An experimental on‐line system ‘MARCAS’ was used to test profile construction and the utility of the various elements in MARC records as search keys. The programs allowed both weighted and Boolean searching on the title and author, LC classification and subject headings, and the BNB Precis indexing terms and Reference Index Numbers. Test profiles were constructed for nine libraries covering a range of subject fields, and run on six weeks of BNB and six weeks of LC MARC tapes. The output was assessed for relevance and recall, and the results analysed in terms of precision and recall for various combinations of searchable fields. The best performance, with recall and precision both about 50%, was given by searching all verbal fields together—title and author, LC subject headings, and (BNB tapes only) Precis indexing terms. Costs for the experimental on‐line system, and a batch version of the system, are identified.

Performing efficient literature searches and subscribing to the most comprehensive databases for interdisciplinary fields can be challenging since the literature is typically indexed in numerous databases to different extents. Comparing databases will help information professionals make appropriate choices when teaching, literature searching, creating online subject guides, and deciding which databases to renew when faced with fiscal challenges. The purpose of this paper is to compare databases for searching the chemical engineering literature.

This paper compares journal indexing and search recall across seven databases that cover the chemical engineering literature in order to determine which database and database pair provide the most comprehensive coverage in this area. It also summarizes published, database comparison methods to aid information professionals in undertaking their own comparative assessments.

SciFinder, Scopus, and Web of Science, listed alphabetically, were the leading databases for searching the chemical engineering literature. SciFinder-Scopus and SciFinder-Web of Science were the top two database pairs. No single database or pair provided 100 percent complete coverage of the literature examined. Searching a second database increased the recall of results by an average of 17.6 percent.

The findings are useful since they identify “best bets” for performing an efficient search of the chemical engineering literature. Information professionals can also use the methods discussed to compare databases for any discipline or search topic.

This paper builds on the previous literature by using a dual approach to compare the coverage of the chemical engineering literature across multiple databases. To the author’s knowledge, comparing databases in the field of chemical engineering has not been reported in the literature thus far.

The purpose of this paper is to highlight the retrieval effectiveness of search engines taking into consideration both precision and relative recall.

The study is based on search engines that are selected on the basis of Alexa (Actionable Analytics for the web) Rank. Alexa listed top 500 sites, namely, search engines, portals, directories, social networking sites, networking tools, etc. But the scope of study is confined to only general search engines on the basis of language which was confined to English. Therefore only two general search engines are selected for the study . Alexa reports Google.com as the most visited website worldwide and Yahoo.com as the fourth most visited website globally. A total of 15 queries were selected randomly from PG students of Department of Library and Information Science during a period of eight days (from May 8 to May 15, 2014) which are classified manually into navigational, informational and transactional queries. However, queries are largely distributed on the two selected search engines to check their retrieval effectiveness as a training data set in order to define some characteristics of each type. Each query was submitted to the selected search engines which retrieved a large number of results but only the first 30 results were evaluated to limit the study in view of the fact that most of the users usually look up under the first hits of a query.

The study estimated the precision and relative recall of Google and Yahoo. Queries using concepts in the field of Library and Information Science were tested and were divided into navigational queries, informational queries and transactional queries. Results of the study showed that the mean precision of Google was high with (1.10) followed by Yahoo with (0.88). While as, mean relative recall of Google was high with (0.68) followed by Yahoo with (0.31), respectively.

The study highlights the retrieval effectiveness of only two search engines.

The research work is authentic and does not contain any plagiarized work.

The purpose was to evaluate the effectiveness of Google (as an international search engine) as well as of Parsijoo, Rismoon, and Yooz (as Persian search engines).

In this research, Google search engine as an international search engine, and three local ones, Parsijoo, Rismoon, and Yooz, were selected for evaluation. Likewise, 32 subject headings were selected from the Persian Subject Headings List, and then simulated work tasks were assigned based on them. A total of 192 students from Ferdowsi University of Mashhad were asked to search for the information needed for simulated work tasks in the selected search engines, and then to copy the relevant website URLs in the search form.

The findings indicated that Google, Parsijoo, Rismoon, and Yooz had a significant difference in the precision, recall, and normalized discounted cumulative gain. There was also a significant difference in the effectiveness (average of precision, recall, and NDCG) of these four search engines in the retrieval of the Persian resources.

Users using an efficient search engine will attain more relevant documents, and Google search engine was more efficient in retrieving the Persian resources. It is recommended to use Google as it has a more efficient search.

In this research, for the first time, Google has been compared with local Persian search engines considering the new approach (simulated work tasks).

The literature of the evaluation of Internet search engines is reviewed. Although there have been many studies, there has been little consistency in the way such studies have been carried out. This problem is exacerbated by the fact that recall is virtually impossible to calculate in the fast changing Internet environment, and therefore the traditional Cranfield type of evaluation is not usually possible. A variety of alternative evaluation methods has been suggested to overcome this difficulty. The authors recommend that a standardised set of tools is developed for the evaluation of web search engines so that, in future, comparisons can be made between search engines more effectively, and that variations in performance of any given search engine over time can be tracked. The paper itself does not provide such a standard set of tools, but it investigates the issues and makes preliminary recommendations of the types of tools needed.

This paper reports on a comparative evaluation of two computerised reference retrieval systems, INSTRUCT and PLEXUS. Instruct is a statistically‐based system based on best match searching and automatic index term weighting while Plexus uses expert systems techniques to improve access to a conventional Boolean search system. After an introduction to the retrieval techniques used by the two systems, their retrieval effectiveness is compared using a set of nineteen queries and 512 documents on the subject of gardening. The best results were obtained by using the terms suggested by the Plexus system as the basis for an Instruct search.