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Semantic technologies are a potential approach to enhancing the use of the web of knowledge. An experiment was conducted to investigate the roles of two semantic techniques, namely concept recommendation and mind maps, for females and males This paper aims to document this research.

The study compared the searching behaviours and perceptions of searching strategies in the search environment with techniques to reveal the gender difference in the use of semantic technologies. The study further investigated how the techniques influenced female and male students' searching experiences by comparing their searching behaviours and strategies in two different environments, one developed with the semantic technologies and one without.

Although the techniques were helpful for both female and male students in improving their perceptions of searching strategies, there were gender differences in sense of disorientation, problem solving and searching patterns. In particular, the techniques facilitated females to search for information beyond similarity holes, but did not demonstrate such an effect on males. However, they supported males to organize information for better use.

The study is only a small‐scale investigation. Further studies need to be conducted with a larger sample to obtain robust evidence.

In this paper, the effects of semantic technologies are evaluated from the perspectives of education and the human factor, rather than only in terms of technical performance.

Consider the prospects for keyword searching with the advent of user‐access to PRISM interlibrary lending system in December 1992. Offers some helpful avice for starting out with PRISM. Considers restrictions to using keyword searching for CAT ME Plus and CAT CD450 users. Outlines keyword commands, keyword searches, character masking, HRR prompt and revise features, error messages and Help as well as Internet access.

Search trees are a set of paths with branches or choices that enable a system to carry out the most sensible search approach at each stage of a search. A new design for subject access to online catalogs enlists search trees to identify the characteristics of end‐user queries for subjects, control system responses, and determine appropriate subject‐searching approaches in response to the subject queries users entered. The purpose of this article is to identify characteristics of the most difficult user queries and recommend enhancements to the new subject‐searching design to enable it to produce useful retrievals in response to the wide variety of queries users pose to online catalogs. Online catalogs governed by search trees are more effective than the users themselves in selecting subject‐searching approaches that would produce useful information for the subjects users seek. The enhanced search trees presented and tested in this article enlist subject‐searching approaches that are not typical of the functionality of operational online catalogs. Design and development is required to upgrade existing online catalogs with search trees and new subject‐searching functionality to be successful in responding with useful retrievals to the most difficult user queries.

In order to compare the value of subject descriptors and title keywords as entries to subject searches, two studies were carried out. Both studies concentrated on monographs in the humanities and social sciences, held by the online public access catalogue of the National Library of the Netherlands. In the first study, a comparison was made by subject librarians between the subject descriptors and the title keywords of 475 records. They could express their opinion on a scale from 1 (descriptor is exactly or almost the same as word in title) to 7 (descriptor does not appear in title at all). It was concluded that 37 per cent of the records are considerably enhanced by a subject descriptor, and 49 per cent slightly or considerably enhanced. In the second study, subject librarians performed subject searches using title keywords and subject descriptors on the same topic. The relative recall amounted to 48 per cent and 86 per cent respectively. Failure analysis revealed the reasons why so many records that were found by subject descriptors were not found by title keywords. First, although completely meaningless titles hardly ever appear, the title of a publication does not always offer sufficient clues for title keyword searching. In those cases, descriptors may enhance the record of a publication. A second and even more important task of subject descriptors is controlling the vocabulary. Many relevant titles cannot be retrieved by title keyword searching because of the wide diversity of ways of expressing a topic. Descriptors take away the burden of vocabulary control from the user.

The purpose of this paper is to explore educational researchers’ online literature searching and sourcing strategies.

Adopting a multiple-case study approach, the authors conducted interviews and compared strategies employed by three groups of researchers: less-experienced doctoral students, experienced doctoral students, and junior faculty.

The results showed that the three groups differed in four searching strategies and two sourcing strategies. The former included: using and modifying keywords, doing advanced searches to narrow down or expand results, chaining, and networking to retrieve literature, while the latter consisted of: evaluating and selecting multiple-source articles, and self-monitoring the multiple-source searching process. The findings also revealed that the experienced doctoral students and junior faculty were able to adopt searching and sourcing strategies flexibly and simultaneously for the purpose of determining more relevant and useful sources. The findings suggest that these researchers, especially the less-experienced students, need specialized training to acquire sourcing strategies in order to critically evaluate relevant information or scholarly work to fulfill their research purposes.

Information seeking, an essential part of scholars’ work, has been widely examined across disciplines. However, few studies have explored scholars’ searching and sourcing behaviors for online academic literature. This study fulfilled the research gap.

This paper intends to examine the antecedents of perceived creativity and flow experience in order to understand how consumers' advertisement keywords browsing influences their searching intentions and/or behaviours regarding purchase. In addition, it aims to consider two kinds of intentions in the theory of planned behaviour (TPB) to facilitate the translation of intentions into behaviour.

Research constructs were drawn from pre‐validated measurement items. An online survey was conducted at my3q.com. A total of 368 surveys were returned. The results were analysed using structural equation modelling with Smart PLS 2.0.

The results show that flow experience positively affects the users' attitude toward keyword searching, the intention to search keywords, controllability, and self‐efficacy. The antecedent belief of perceived creativity also positively influences the attitude toward keyword searching. The overall TPB model is effective in terms of predicting consumers' online keyword search behaviours; the intention to purchase a product especially affects a consumer's intention to search keywords online.

To attract consumers companies have to use combined marketing strategies to provide creative advertisements to make their products look appealing. Moreover, advertisements that are fun and make people feel curious would also be appealing and make the consumers feel that they are able or resourceful enough to find the keywords.

Two kinds of intentions – intention to purchase a product and intention to search keywords online – are simultaneously considered in this study. Moreover, the combination of flow theory, perceived creativity and TPB demonstrates an appropriate theoretical basis to examine consumers' online keyword search behaviours.

Purpose – The main purpose of this research is to determine whether the performance of natural language (NL) search engines in retrieving exact answers to the NL queries differs from that of keyword searching search engines. Design/methodology/approach – A total of 40 natural language queries were posed to Google and three NL search engines: Ask.com, Hakia and Bing. The first results pages were compared in terms of retrieving exact answer documents and whether they were at the top of the retrieved results, and the precision of exact answer and relevant documents. Findings – Ask.com retrieved exact answer document descriptions at the top of the results list in 60 percent of searches, which was better than the other search engines, but the mean value of the number of exact answer top list documents for three NL search engines (20.67) was a little less than Google's (21). There was no significant difference between the precision for Google and three NL search engines in retrieving exact answer documents for NL queries. Practical implications – The results imply that all NL and keyword searching search engines studied in this research mostly employ similar techniques using keywords of the NL queries, which is far from semantic searching and understanding what the user wants in searching with NL queries. Originality/value – The results shed light into the claims of NL search engines regarding semantic searching of NL queries.