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Investigates image search engines (ISEs) on the Internet. A total of 23 ISEs were examined in an attempt to investigate, evaluate, and characterise their common features. Each individual ISE was evaluated against the common features. Attempts to summarise the most comprehensive and complete ISE by looking at their significant features.

This paper describes an investigation of 20 different meta‐search engines. Their features were characterised and classified into six distinct categories based on their functionality and use. The most used features and unique features were specified and explained in detail. The findings of this study will benefit both meta‐search‐engine developers and ordinary search users.

The aims of this study were to identify the retrieval features for online databases; difficulties faced by users; and retrieval features expected by users. A total of 25 databases were surveyed and 40 users were interviewed after the training sessions. Common retrieval features included Boolean operators, phrase searching, match of exact words or phrases, field specific and limit fields searches, truncation, and wildcard. Even though features are offered in many systems, their interpretation and implementation are different. Unique features included lateral searching, density and frequency of terms, reference link, and searching via table of content. The expected features included relevance feedback and term weighting other than those already offered by ACM Digital Library and IEEE Xplore. Such expectations were influenced by the users' background in ICT. Difficulties included application of the retrieval features in searching. Database providers must include the expected features, synonyms linked to terms in the thesaurus, and extensive search examples.

Current research topics in relation to health information searching focus on challenges faced by health consumers and domains used to perform the health search. Health consumers may not be capable of successfully searching for a health task due to limited medical knowledge. As such search assisting features provided on health domains are important in assisting health consumers during a search session. The purpose of this paper is to perform a preliminary exploratory research study to understand if search assisting features are visible to searchers and the usage of search assisting features when searching on a personal health task.

A convenience sampling method in a university setting and an observational type study was used. MedlinePlus is used as the search domain for this research study. While participants of this research study were first time users of MedlinePlus, they were not first time medical searchers.

Results of this research study indicate health consumers do not utilize search assisting features when searching for a personal health task. This is because health consumers are comfortable with their search skills. In other cases health consumers found the search assisting features irrelevant or had no confidence in the search assisting features presented. Key contributions of this research study indicate health consumers do not utilize search assisting features when searching for a personal health task. This is because health consumers are comfortable with their search skills. In other cases health consumers found the search assisting features irrelevant or had no confidence in the search assisting features presented.

Results of this research study has implications for health domain and human computer designers in relation to the development of specialized search assisting features and the placement of these features. Theoretical contributions indicate health searchers use search assisting features minimally when searching on a personal health task.

Results of this research study indicate health consumers do not utilize search assisting features when searching for a personal health task. This is because health consumers are comfortable with their search skills. In other cases health consumers found the search assisting features irrelevant or had no confidence in the search assisting features presented.

The purpose of this paper is to evaluate Help features in digital libraries and identify problems related to their design.

This study selects six digital libraries to represent a variety of digital libraries developed or sponsored by different types of organisations. The Help features of these selected digital libraries are examined by their types (explicit versus implicit), formats (texts, images, screenshots, multimedia materials, and interactive formats), and presentation styles (descriptive, guided, procedural, and exemplary).

This study presents the types of Help features available in the selected digital libraries, and further characterises the formats and presentation styles of these Help features. In the process of analysis, the author also identifies six types of problems: lack of standards; tradeoff between using explicit Help and implicit help; tradeoff between using general Help versus specific Help; lack of interactive Help features; lack of dynamic presentation styles; and lack of Help features for advanced users and users who do not understand English.

In order to design Help features that facilitate users to effectively use digital libraries, further research needs to extend studies to what types of help‐seeking situations users generally encounter and the corresponding support they need.

This study provides insightful information regarding the current status and problems of the Help features in existing digital libraries.

The study aims to paint a representative picture of the current state of search interfaces of Swedish online museum collections, focussing on search functionalities with particular reference to subject searching, as well as the use of controlled vocabularies, with the purpose of identifying which improvements of the search interfaces are needed to ensure high-quality information retrieval for the end user.

In the first step, a set of 21 search interface criteria was identified, based on related research and current standards in the domain of cultural heritage knowledge organization. Secondly, a complete set of Swedish museums that provide online access to their collections was identified, comprising nine cross-search services and 91 individual museums' websites. These 100 websites were each evaluated against the 21 criteria, between 1 July and 31 August 2020.

Although many standards and guidelines are in place to ensure quality-controlled subject indexing, which in turn support information retrieval of relevant resources (as individual or full search results), the study shows that they are not broadly implemented, resulting in information retrieval failures for the end user. The study also demonstrates a strong need for the implementation of controlled vocabularies in these museums.

This study is a rare piece of research which examines subject searching in online museums; the 21 search criteria and their use in the analysis of the complete set of online collections of a country represents a considerable and unique contribution to the fields of knowledge organization and information retrieval of cultural heritage. Its particular value lies in showing how the needs of end users, many of which are documented and reflected in international standards and guidelines, should be taken into account in designing search tools for these museums; especially so in subject searching, which is the most complex and yet the most common type of search. Much effort has been invested into digitizing cultural heritage collections, but access to them is hindered by poor search functionality. This study identifies which are the most important aspects to improve.

This paper aims to investigate the multiple language support features in internet search engines. The diversity of the internet is reflected not only in its users, information formats and information content, but also in the languages used. As more and more information becomes available in different languages, multiple language support in a search engine becomes more important.

The first step of this study is to conduct a survey about existing search engines and to identify search engines with multiple language support features. The second step is to analyse, compare, and characterise the multiple language support features in the selected search engines against the proposed five basic evaluation criteria after they are classified into three categories. Finally, the strengths and weaknesses of the multiple language support features in the selected search engines are discussed in detail.

The findings reveal that Google, EZ2Find, and Onlinelink respectively are the search engines with the best multiple language support features in their categories. Although many search engines are equipped with multiple language support features, an indispensable translation feature is implemented in only a few search engines. Multiple language support features in search engines remain at the lexical level.

The findings of the study will facilitate understanding of the current status of multiple language support in search engines, help users to effectively utilise multiple language support features in a search engine, and provide useful advice and suggestions for search engine researchers, designers and developers.

The purpose of the paper is to examine the various features and components of web‐based online public access catalogues (OPACs) of IIT libraries in India with the help of a specially designed evaluation checklist.

The various features of the web‐based OPACs in six IIT libraries (IIT Delhi, IIT Bombay, IIT Madras, IIT Kanpur, IIT Guwahati, and IIT Roorkee) are evaluated. The evaluation approach taken was similar to that of Luong and Liew with minor modifications, comprising 122 dichotomous questions with 174 features and categorized as 11 broad categories.

The study explored different features of web‐based OPACs, of which page layout received the highest average scores with 93.33 percent, followed by the general features category with 90 percent. In contrast, session filters was the weakest category with only 40.47 percent. The results indicated that some web‐based OPACs reached the maximum scores for some categories. The results also indicated that VTLS‐based and LibSys‐based OPACs had the higher score on average (74.7 percent) and the iitKlas‐based OPAC of IITK received the lowest score of 44.2 percent. None were rated excellent. Only 50 percent of the web‐based OPACs studied achieved an above average ranking, of which Indian Institute of Technology, Madras (IITM) had the highest total score (131), and the Indian Institute of Technology, Kanpur (IITK) had the lowest total score (77). Almost all of the web OPACs studied lacked federated search, adjunct thesaurus help and spell check facilities, which seems to raise many questions regarding the facilities provided in the OPAC 2.0 environment of today and hence needs to be addressed as a priority in the subsequent generations of the web‐based OPACs and their development.

It is hoped that the libraries at the IITs will attend to the lacunae and soon develop fully functional web‐based OPACs with Web 2.0 and 3.0 technologies.

The findings of the study will not only guide study librarians and other newly established institutions but also ILMS vendors, so that they can overcome the limitations faced by users and improve their products as OPAC 2.0. This will also help the in‐house web‐based OPACs of IIT Kanpur and IIT Roorkee to compete with other reputed ILMS‐based OPACs.

The purpose of this paper to investigate the effectiveness of selected search features in the major English and Chinese search engines and compare the search engines’ retrieval effectiveness.

The search engines Google, Google China, and Baidu were selected for this study. Common search features such as title search, basic search, exact phrase search, PDF search, and URL search, were identified and used. Search results from using the five features in the search engines were collected and compared. One‐way ANOVA and regression analysis were used to compare the retrieval effectiveness of the search engines.

It was found that Google achieved the best retrieval performance with all five search features among the three search engines. Moreover Google achieved the best webpage ranking performance.

The findings of this study improve the understanding of English and Chinese search engines and the differences between them in terms of search features, and can be used to assist users in choosing appropriate and effective search strategies when they search for information on the internet.

The original contributions of this paper are that the Chinese and English search engines in both languages are compared for retrieval effectiveness. Five search features were evaluated, compared, and analysed in the two different language environments by using the discounted cumulative gain method.

This paper reports on a study conducted to develop a framework for evaluating the retrieval features using an applied ethnographic method. Direct observation, interviews, analysis of notes, and informal social interaction were done with ten users on their application of the retrieval features and their difficulties in searching. Retrieval features evaluated were those offered by 12 database providers. Findings revealed that the proposed framework successfully gathered the data needed. Application of the features was related to users' retrieval tasks, preference and style of searching, and understanding of the features. Difficulties were related to identification of the appropriate search terms. Expected retrieval features were related to search terms, i.e. relevance feedback, list of similar terms, and assigning values to search terms. Applied ethnographic method used in this study revealed that users have a substantial amount of knowledge about the retrieval features, and that their comments were related to their subject background.