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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.

The purpose of this paper is to investigate image search and retrieval problems in selected search engines in relation to Persian writing style challenges.

This study is an applied one, and to answer the questions the authors used an evaluative research method. The aim of the research is to explore the morphological and semantic problems of Persian language in connection with image search and retrieval among the three major and widespread search engines: Google, Yahoo and Bing. In order to collect the data, a checklist designed by the researcher was used and then the data were analyzed by descriptive and inferential statistics.

The results indicate that Google, Yahoo and Bing search engines do not pay enough attention to morphological and semantic features of Persian language in image search and retrieval. This research reveals that six groups of Persian language features include derived words, derived/compound words, Persian and Arabic Plural words, use of dotted T and the use of spoken language and polysemy, which are the major problems in this area. In addition, the results suggest that Google is the best search engine of all in terms of compatibility with Persian language features.

This study investigated some new aspects of the above-mentioned subject through combining morphological and semantic aspects of Persian language with image search and retrieval. Therefore, this study is an interdisciplinary research, the results of which would help both to offer some solutions and to carry out similar research on this subject area. This study will also fill a gap in research studies conducted so far in this area in Farsi language, especially in image search and retrieval. Moreover, findings of this study can help to bridge the gap between the user’s questions and search engines (systems) retrievals. In addition, the methodology of this paper provides a framework for further research on image search and retrieval in databases and search engines.

The purpose of this paper is to develop a search engine dedicated to image retrieval in a bilingual (French and English) context. This paper presents the first phase of user testing that was carried out to validate and refine SINCERITY, the new search device.

This first phase of the search engine testing involved a small group of image searchers (10 French-speaking and 10 English-speaking participants) who were asked to retrieve a sample of images (30) using the new tool. A questionnaire was also developed to compile the comments of the users.

The results of this first phase of testing revealed that even though image indexing was sometimes problematic, the participants did not encounter major difficulties retrieving images with SINCERITY. Comments and suggestions received will be taken into consideration to improve the performance and aesthetics of the search engine.

Once fully operational, SINCERITY will allow users to search images in an attractive and user-friendly manner. Eventually, other types of images (documentary and artistic) will be added to the image database linked to the image search engine, as well as other languages.

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.

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.

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.

The study only takes into consideration basic image search feature, i.e. text-based search.

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.

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.

Image searching is a common activity for web users. Search engines offer image retrieval services based on textual queries. Previous studies have shown that web searching is more demanding when the search is not in English and does not use a Latin‐based language. The aim of this paper is to explore the behaviour of the major search engines in image retrieval using Greek text queries and to present and evaluate an image metaseacher that combines semantically similar queries to improve the relevance in image retrieval.

Initially the image retrieval capabilities (based on the number of items retrieved and their relevance) of search engines in Greek queries is studied with a number of semantically similar queries which differ in morphology. Then a system that produces semantically similar queries and merges their results is presented and the increase in relevance is measured. For the purpose of this paper, a number of queries suggested by a few students are run through the presented metasearcher and directly in the search engines. The participants of the evaluation study measured the precision in both cases.

The initial evaluation revealed that search engines retrieve different results in queries that differ in morphology or in grammar but still express exactly the same information need. Omission of diacritics affects the retrieval negatively as well. The study showed that the number of relevant images increases by combining the results of queries that differ in morphology.

The findings of this study could be applicable to other complex non‐Latin languages based, for example, on the Cyrillic alphabet. The presented metasearcher is a framework on how to expand the image retrieval capabilities of existing search engines. Its modular nature allows the straightforward integration of other techniques that are tailored to the characteristics of specific natural languages.

The purpose of this paper is to present the results of the first phase of a research project that aims to develop a bilingual interface for the retrieval of digital images. The main objective of this extensive exploration was to identify the characteristics and functionalities of existing search interfaces and similar tools available for image retrieval.

An examination of 159 resources that offer image retrieval was carried out. First, general search functionalities offered by content-based image retrieval systems and text-based systems are described. Second, image retrieval in a multilingual context is explored. Finally, the search functionalities provided by four types of organisations (libraries, museums, image search engines and stock photography databases) are investigated.

The analysis of functionalities offered by online image resources revealed a very high degree of consistency within the types of resources examined. The resources found to be the most navigable and interesting to use were those built with standardised vocabularies combined with a clear, compact and efficient user interface. The analysis also highlights that many search engines are equipped with multiple language support features. A translation device, however, is implemented in only a few search engines.

The examination of best practices for image retrieval and the analysis of the real users' expectations, which will be obtained in the next phase of the research project, constitute the foundation upon which the search interface model that the authors propose to develop is based. It also provides valuable suggestions and guidelines for search engine researchers, designers and developers.

This paper aims to present the third stage of a research project that aims to develop a bilingual interface for the retrieval of digital images. The requirements and implementation of the search engine are described. Image search engines attempt to give access to a range of online images available on the web.

The strategy of using open-source software components as much as possible was chosen for the advantages of this approach: low initial cost and accessibility to evaluate and develop enhancements independently and driven by research objectives rather than financial viability.

Open-source software components can be used to develop the interface. The implementation of the image search engine and its indexes uses: Apache Solr, AJAX-Solr, jsTree and jQuery. Microsoft Translator web service was integrated into the interface to provide the optional user query translation.

The search interface is intended to be an innovative tool for image searchers who are looking for digital images. The search interface gives the image searchers the opportunity to easily access a variety of visual resources and facilitates searching for images in two different languages (English and French).

Internet-based marketing communication has been an important element for organizations to build brand image and brand equity. Higher education is not an exception. However, configuring the right mix in the age of social networking sites and various online displays and constantly changing algorithm in search engine optimization have become major challenges today. Hence, the purpose of this study is to configure integrated online marketing communication for the development of brand image and brand equity for higher educational institutions.

The study is quantitative in nature. A responsive group of 370 students was chosen from different educational institutions in Malaysia via stratified random sampling techniques. Both exploratory and confirmatory factor analyses were used for interpreting the data. To test the derived hypotheses, structural equation modelling was used.

In line with contemporary literature, the study revealed positive relationships between brand image and brand equity, between search engine and brand image and between social media and brand image. The relationship between online display and brand image was not found significant.

Future research can be done considering both online and conventional marketing communications for the same purpose. This approach can also be used for private and public institutions separately, considering their differences in nature.

Because history and tradition are no more a single tool to attain and retain the positive image and customer-based brand equity, this study can help higher educational institutions to configure integrated online communication for their target groups, such as students and industry, in the age of the internet.

This study generates a comprehensive understanding of the impact of Web-based marketing communication to develop brand image and brand equity of higher educational institutions.

The purpose of this study aims to identify the impact of verbal-visual cognitive styles on the level of satisfaction and behavior in the textual and content search of Google Images.

“Riding” cognitive style test and satisfaction questionnaire were used as data collection tools. Also, to collect data related to the image search behavior, the subjects’ transaction files were recorded using Camtasia software and then the files observed and reviewed. The research sample was 90 postgraduate students of Shiraz University.

The results showed that cognitive styles in interaction with the text-based and content-based search system of “Google Images” affected user’s satisfaction. Text-based image retrieval, in which vocabulary-based information needs were expressed, was more compatible with the verbal cognitive style and resulted in greater satisfaction. In contrast, in content-based image retrieval, where it was possible to express information needs in the form of images, users were more satisfied with the visual cognitive style. Verbal users performed more positively in text-based search and visual users in content-based search.

Considering the research gap, which has identified the performance of visual text-based and content-based systems in terms of satisfaction and cognitive style search behavior, the present study could be considered a small effort to promote science.

The purpose of this paper is to examine the way in which end user searching on the web has become the primary method of locating digital images for many people. This paper seeks to investigate how users structure these image queries.

This study investigates the structure and formation of image queries on the web by mapping a sample of web queries to three known query classification schemes for image searching (i.e. Enser and McGregor, Jörgensen, and Chen).

The results indicate that the features and attributes of web image queries differ relative to image queries utilized on other information retrieval systems and by other user populations. This research points to the need for five additional attributes (i.e. collections, pornography, presentation, URL, and cost) in order to classify web image queries, which were not present in any of the three prior classification schemes.

Patterns in web searching for image content do emerge that inform the design of web‐based multimedia systems, namely, that there is a high interest in locating image collections by web searchers. Objects and people images are the predominant interest for web searchers. Cost is a factor for web searching. This knowledge of the structure of web image queries has implications for the design of image information retrieval systems and repositories, especially in the area of automatic tagging of images with metadata.

This is the first research that examines whether or not one can apply image query classifications schemes to web image queries.