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The aim of this study is to explore to which extent searching by medical students in Medline produces information items useful for writing an essay measured by precision and relative recall as perceived by the students, the proportion of cited items, and their utilization on four dimensions of the essay writing task evaluated by external assessors. It also aims to study interrelations of search process and outcome.

The study subjects were 42 third year medical students attending a class on Diagnostic and therapy. Searching in Medline was a part of their assignment of essay writing. The data consist of students' printed logs of Medline searches, students' assessments of the usefulness of the references retrieved, a questionnaire concerning the search process, and evaluation scores of the essays given by the teachers of the class. Pearson correlation coefficients were calculated for answering the research questions.

The paper finds that precision and relative recall were not associated with evaluation scores in three of the four dimensions assessed. Some of the process variables were associated with precision and with assessment scores in two of the four dimensions assessed. Citing rate was negatively associated with recall. It seems that precision and recall are only weakly, if at all, associated to the use of information in the documents retrieved for writing the essay. Precision and relative recall are not associated to the way information in the retrieved items is used for performing the task. Users evidently look for a sufficient number of documents containing enough information for progressing in their task. Precision and recall are not sufficient measures in evaluating IR systems, but they have to be completed by other measures indicating the impact of the system on users’ task performance.

The paper provides useful information on students' information search process.

Some parameters and techniques in use for describing the results of tests on IR systems are analysed. Several considerations outside the scope of the usual 2 x 2 table are relevant to the choice of parameters. In particular, a variable which produces a ‘performance curve’ of a system corresponds to an extension of the 2 x 2 table. Also, the statistical relationships between parameters are all‐important. It is considered that precision is not such a useful measure of performance (in conjunction with recall) as fallout. A more powerful alternative to Cleverdon's ‘inevitable inverse relationship between recall and precision’ is proposed and justified, namely that the recall‐fallout graph is convex.

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”

It is now ten years since some slight experimental evidence was presented which appeared to support the hypothesis that there was an inverse relationship between recall and precision. The idea of this was certainly not new; Fairthorne had more than implied it in his discussions on OBNA and ABNO systems, i.e. Only‐But‐Not‐All (high precision) and All‐But‐Not‐Only (high recall). However, it was one of the propositions arising from Cranfield I which met with strong opposition and was quite rightly attacked. In reply to the critical review by Swanson, I had to agree that the simple hypothesis required modification. By the following year test results coming from the experiments by Salton and from Cranfield II made further modification necessary, and the hypothesis was finally put forward to read as follows: ‘Within a single system, assuming that a sequence of sub‐searches for a particular question is made in the logical order of expected decreasing precision, and the requirements are those stated in the question, there is an inverse relationship between recall and precision, if the results of a number of different searches are averaged. This, it will be noted, has four important qualifications to the basic statement.

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.

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.

Term position information, as provided in some Boolean systems in the form of field restriction and term proximity, is reviewed and its value assessed. Non‐Boolean retrieval in the form of the ranked output experiment has not so far used term position information but has concentrated on schemes of term weighting. The use of term proximity devices is proposed here by analogy with Boolean techniques and seven algorithms are devised to incorporate the ideas of sentence matching, proximate terms, term order specification and term distance computations. It is hypothesised that term position will act as a precision device. A new search experiment is then described in which a test collection is processed into sentences and then output ranking using term position is obtained. Results are given for five algorithms compared against quorum searching as the benchmark. The best result increased the precision ratio by 18% and used proximate matching term pairs in sentences plus a distance component.

The purpose of this paper is to present an extension to a framework based on the information structure (IS) model for combining information filtering (IF) results. The main goal of the framework is to combine the results of the different IF systems so as to maximise the expected payoff (EP) to the user. In this paper we compare three different approaches to tuning the relevance thresholds of individual IF systems that are being combined in order to maximise the EP to the user. In the first approach we set the same threshold for each of the IF systems. In the second approach the threshold of each IF system is tuned independently to maximise its own EP (“local optimisation”). In the third approach the thresholds of the IF systems are jointly tuned to maximise the EP of the combined system (“global optimisation”).

An empirical evaluation is conducted to examine the performance of each approach using two IF systems based on somewhat different filtering algorithms (TFIDF, OKAPI). Experiments are run using the TREC3, TREC6, and TREC7 test collections.

The experiments reveal that, as expected, the third approach always outperforms the first and the second, and that for some user profiles, the difference is significant. However, operational goals argue against global optimisation, and the costs of meeting these operational goals are discussed.

One limitation is the assumption of independence of the IF systems: in real life systems usually use similar algorithms, so dependency might occur. The approach also tends to be examined with the assumption of dependency between systems.

The main practical implications of this study lie in the empirical proof that combination of filtering systems improves filtering results and the finding about the optimal combination methods for the different user profiles. Many filtering applications exist (e.g. spam filters, news personalisation systems, etc.) that can benefit from these findings.

The study presents and compares the contribution of three different combination methods of filtering systems to the improvement of filtering results It empirically shows the benefits of each method and draws important conclusions about the combination of filtering systems.

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.

An index language usually incorporates various methods for improving recall and/or precision when searching. Recall devices tend to increase the size of retrieved document sets, while precision devices tend to reduce them. The most common recall and precision devices are described in general terms and their usage in several thesauri is examined. The thesauri looked at relate to databases available for searching in the ESA IRS online information system at one time or another and include the NASA Thesaurus; Thesaurus of Engineering and Scientific Terms; Thesaurus of Metallurgical Terms; Subject Headings used by the USAEC; Subject Headings for Engineering; INIS Thesaurus and the INSPEC Thesaurus. The extent to and the way in which the recall and precision devices are used in the ESA IRS online system for controlled and uncontrolled subject term searching are discussed.