Search results

Suggested tag was considered as one of the critical factors affecting a user’s tagging behaviour. However, compared to the findings on the suggested tags for the monolingual environment, it still lacks focused studies on the tag suggestions for cross-language information. Therefore, this paper aims to concern with annotation behaviour and psychological cognition in the cross-language environment when suggested tags are provided.

A cross-language tagging experiment was conducted to explore the impact of suggested tags on the tagging results and process. The descriptive statistics of tags, the sources and semantic relations of tags, as well as the user’s psychological cognition were all measured in the test.

The experimental results demonstrated that the multilingual suggested tags could bring some costs to a user’s tagging perception. Furthermore, the language factor of suggested tags led to different paths of tagging imitation (reflected by longer semantic mapping and imitation at the visual level) and different cognitive processes (topic extraction and inference process).

To the best of the authors’ knowledge, this study is one of the first to emphasize the effect of suggested tags during multilingual tagging. The findings will enrich the theories of user-information interaction in the cross-language environment and, in turn, provide practical implications for tag-based information system design.

The purpose of this paper is to report the results and the methods of a study which applied grounded theory to the information-seeking behaviour of social scientists when searching Arabic and English academic databases using both languages.

The research applied the grounded theory approach using search experiments and semi-structured interviews. Think-aloud protocol during the experiment was used to capture the data from the subjects to allow a detailed analysis for the experiment. The semi-structured interviews followed each experiment and were analysed using the Strauss and Corbin (1990) version of the grounded theory, as were the think-aloud protocols.

The results of the think-aloud protocols and the semi-structured interviews suggest that the information needs of the subjects varied depending on the language used. In addition, it was discovered that social scientists followed more tactics in searching the Arabic database for the same tasks searched in English during the experiment. This allowed more search strategies and search tactics to appear in seeking information in Arabic language. The study also proposed a model to account for the cross-language information-seeking behaviour.

This study identifies and compares the information-seeking behaviour of the social scientists in Jordanian universities in searching both Arabic and English academic databases. Therefore, the findings of this study cannot be generalized to other Arab countries, unless there was similar context.

Few studies have investigated information-seeking behaviour using academic Arabic databases and proposed information-seeking behaviour models. No studies have compared information-seeking behaviour when using Arabic and English academic databases. The value of the current study arises by being the first study to identify and compare the information-seeking behaviour of social scientists by using grounded theory and proposing a cross-language information-seeking behaviour model.

Less attention has been paid to users’ interactions and behavior in studying multilingual search. Although digital library researchers have yet to assess user interaction and behavior in multilingual search, they have concurred that there is a need for user studies that document the extent to which information retrieval systems meet multilingual users’ needs and expectations. The paper aims to discuss these issues.

This study is composed of five individual cases. The case study participants were Saudi students enrolled either at a large state university or Historically Black College and University located in the same community. Research questions are, what do Saudi Digital Library (SDL) users experience when searching within the SDL in Arabic and English? And what strategies do they use if they fail to find resources? Data collected for this study were via a qualitative method called video-stimulated recall.

In the Arabic search tasks, participants realized that finding resources is not easy. Participants expressed their concerns about the lack of relevance and accuracy of results returned by the search system, indicating weak trust and confidence in the search system. Whereas in the English search task, participants felt more satisfied and confident in their ability to trust the results returned from the search system. Participants expressed their satisfaction in the search experience as it provided them with accurate and varying resources. The participants faced difficulties finding Arabic resources than English resources in the SDL.

This study is considered one of the earliest works in studying the information-seeking behavior of multilingual digital libraries in the Arabic language. The value of this study arises as being the first study to investigate and report the information-seeking behavior of SDL users.

Citizens Advice Bureau (SHIL in Hebrew) is an information and referral service dedicated to serving the needs of citizens by providing easy access to information about citizenship rights and obligations. Many people turn to the offices of SHIL either for help or to volunteer as advisors. This study seeks to examine the information seeking behavior of SHIL volunteers supplying information services to citizens.

The theoretical foundations of the study are based on two existing models of information searching related to everyday life problems, Foster's non‐linear model of information seeking behavior and Bates's berry‐picking approach. This research employs a qualitative method. A total of 35 advisors in different SHIL branches were interviewed and the content of the interviews was analyzed, mapped and organized into categories by using concepts and terms revealed in the data.

Findings show that volunteers at SHIL search information in a way that integrates the two models mentioned above, the berry‐picking model and the non‐linear model. In addition, findings point to difficulties that the advisors face in solving problems of the clients. These difficulties are connected with the different aspects relating to the flow of information both within and outside the organization and with organizational and administrative aspects at SHIL.

The information seeking behavior of volunteers acting as providers of information services has yet to be investigated at length and the understanding of their information behavior can be of value, since volunteering carries great importance in a democracy.

Graphic-based tag clouds aim to visually represent tag content and tag structure, and then to better represent tagged information for later search. However, few studies have clarified the features among varied visualization approaches involved in graphic-based tag clouds and compared them for the purpose of information search.

After reviewing four kinds of graphic-based tag clouds, an experimental demonstration was conducted in our study to verify how user performs in information search for a general seeking task by using them. Precision ratio, recall ratio, clicks on search and time for search were four variables tested in the experiment. Also, two supplementary tests were respectively carried out to manifest how graphic-based tag clouds contributed to the identification of target tags and tag clusters.

The experimental results showed that compared to tag content visual tag structure was more important to find related tags from tag clouds for information search. In addition, tag clouds that visually represented the semantic relationships within tags could make user more confident about their search result and carry out a shorter learning process during searching, which signified a tag-based information search path when visual elements were applied.

This research is one of the first to illustrate systematically the graphic-based tag clouds and their impacts on information search. The research findings could suggest on how to build up more effective and interactive tag clouds and make proposition for the design of search user interface by using graphic-based tag clouds.

This study aims to discover how domain familiarity and language affect the cognitive load and the strategies applied for the evaluation of search engine results pages (SERP).

This study used an experimental research design. The pattern of the experiment was based upon repeated measures design. Each student was given four SERPs varying in two dimensions: language and content. The criteria of students to decide on the three best links within the SERP, the reasoning behind their selection, and their perceived cognitive load of the given task were the repeated measures collected from each participant.

The evaluation criteria changed according to the language and task type. The cognitive load was reported higher when the content was presented in English or when the content was academic. Regarding the search strategies, a majority of students trusted familiar sources or relied on keywords they found in the short description of the links. A qualitative analysis showed that students can be grouped into different types according to the reasons they stated for their choices. Source seeker, keyword seeker and specific information seeker were the most common types observed.

This study has an international scope with regard to data collection. Moreover, the tasks and findings contribute to the literature on information literacy.

This paper aims to describe a study of the queries generated from a user experiment for cross‐language information retrieval (CLIR) from a historic image archive.

A controlled lab‐based user study was carried out using a prototype Italian‐English image retrieval system. Participants were asked to carry out searches for 16 images provided to them, a known‐item search task. Italian speaking users generated 618 queries for a set of known‐item search tasks. User's interactions with the system were recorded and queries were analysed manually quantitatively and qualitatively. The queries generated by user's interaction with the system were analysed and the results used to suggest recommendations for the future development of cross‐language retrieval systems for digital image libraries.

Results highlight the diversity in requests for similar visual content and the weaknesses of machine translation for query translation. Through the manual translation of queries the authors show the benefits of using high‐quality translation resources. The results show the individual characteristics of users while performing known‐item searches and the overlap obtained between query terms and structured image captions, highlighting the use of user's search terms for objects within the foreground of an image.

This research looks in depth into one case of interaction and one image repository. Despite this limitation, the discussed results are likely to be valid across other languages and image repositories.

To develop effective systems requires studying user's search behaviours, particularly in digital image libraries.

The growing quantity of digital visual material in digital libraries offers the potential to apply techniques from CLIR to provide cross‐language information access services. The value of this paper is in the provision of empirical evidence to support recommendations for effective cross‐language image retrieval system design.

The purpose of this paper is to develop a cross‐language personalized recommendation model based on web log mining, which can recommend academic articles, in different languages, to users according to their demands.

The proposed model takes advantage of web log data archived in digital libraries and learns user profiles by means of integration analysis of a user's multiple online behaviors. Moreover, keyword translation was carried out to eliminate language dissimilarity between user and item profiles. Finally, article recommendation can be achieved using various existing algorithms.

The proposed model can recommend articles in different languages to users according to their demands, and the integration analysis of multiple online behaviors can help to better understand a user's interests.

This study has a significant implication for digital libraries in non‐English countries, since English is the most popular language in current academic articles and it is a very common phenomenon for users in these countries to obtain literatures presented by more than one language. Furthermore, this approach is also useful for other text‐based item recommendation systems.

A lot of research work has been done in the personalized recommendation area, but few works have discussed the recommendation problem under multiple linguistic circumstances. This paper deals with cross‐language recommendation and, moreover, the proposed model puts forward an integration analysis method based on multiple online behaviors to understand users' interests, which can provide references for other recommendation systems in the digital age.

With the increasing number of online multilingual resources, cross-language information retrieval (CLIR) has drawn much attention from the information retrieval (IR) research community. However, few studies have examined how and why multilingual searchers seek information in two or more languages, specifically how they switch and mix language in queries to get satisfying results. The purpose of this paper is to focus on Chinese–English bilinguals’ intra-sentential code-switching behaviors in online searches. The scenarios and reasons of code-switching, factors that may affect code-switching, the patterns of mixed language query formulation and reformulation and how current IR systems and other search tools can facilitate such information needs were examined.

In-depth semi-structured interviews were used as the research method. In total, 30 participants were recruited based on their English proficiency, location and profession, using a purposive sampling method.

Four scenarios and four reasons for using Chinese–English mixed language queries to cover information needs were identified, and results suggest that linguistic and cultural/social factors are of equivalent importance in code-switching behaviors. English terms and Chinese terms in queries play different roles in searches, and mixed language queries are irreplaceable by either single language queries or other search facilitating features. Findings also suggest current search engines and tools need greater emphasis in the user interface and more user education is required.

This study presents a qualitative analysis of bilinguals’ code-switching behaviors in online searches. Findings are expected to advance the theoretical understanding of bilingual users’ search strategies and interactions with IR systems, and provide insights for designing more effective IR systems and tools to discover multilingual online resources, including cross-language controlled vocabularies, personalized CLIR tools and mixed language query assistants.