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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.

This paper seeks to examine the further integration of machine translation technologies with cross language information access in providing web users the capabilities of accessing information beyond language barriers. Machine translation and cross language information access are related technologies, and yet they have their own unique contributions in handling information in multiple languages. This paper aims to demonstrate that there are many opportunities to further integrate machine translation with cross language information access, and the combination can greatly empower web users in their information access.

Using English and Chinese as the language pair for studying, this paper looks at machine translation in query translation‐based cross language information access at multiple important aspects, which include query translation, relevance feedback, interactive cross language information access, out‐of‐vocabulary term translation, and data fusion. The goal is to obtain more insights about the wide range usages of machine translation in cross language information access, and to help the community to identify promising future directions for both machine translation and cross language access.

Machine translation can be applied effectively in many places in the whole cross language information access process. Queries translated by a machine translation system are high quality and are more robust in handling potential untranslated terms. Translation enhancement, a relevance feedback method using machine translation generated returned documents, is not only a valid technique by itself, but also helps to generate more robust cross language information access performance when combined with other relevance feedback techniques. Machine translation is also found to play a significant role in resolving untranslated terms and in data fusion.

This set of comparative empirical studies on integrating machine translation and cross language information access was performed on a common evaluation framework, and examined integration at multiple points of the cross language access process. The experimental results demonstrate the value of further integrating machine translation in cross language information access, and identify interesting future directions for both machine translation and cross language information access research.

Together, increasing globalization and the internet created fertile grounds for the establishment of multilingual digital libraries. Providing cross‐lingual access to materials is of particular interest to political entities such as the European Union, which currently has 23 official languages, but also to multinational companies and countries that have different languages represented among their citizens. The main objective of this paper is to review the literature on multilingual digital libraries and provide an overview of this area.

Based on a thorough literature search in four different databases, a core set of literature on multilingual digital libraries was retrieved. Literature on various aspects of this topic was reviewed. The paper is organized based on emerging themes directly drawn from the literature. Where warranted additional literature is brought in to provide necessary background information or clarification.

Creating a multilingual digital library is a highly complex undertaking and typically requires a collaborative effort between different organizations and people with different areas of expertise. Enabling users to search across languages requires translation resources to cross the language barrier, which can be challenging depending on the language and resource availability. Additional challenges were found to be in data management (localization and language processing), representation (dealing with different fonts and character codes), development (creating international software, cross‐cultural collaboration), and interoperability (system architecture and data sharing). Research in multilingual digital libraries was mostly system based involving experimental systems or system prototypes.

Most likely the literature review does not include all possible journal articles on multilingual digital libraries even though the literature searches done to obtain these articles were thorough and deliberate. Journal articles without the descriptors used in this search and those articles not indexed in the four different databases used in the search will not be included here. The review excludes cross‐language information retrieval research unless it is directly related to existing multilingual digital libraries, or a connection to digital libraries in general is made in the paper itself.

This paper provides the first literature review on the topic of multilingual digital libraries and provides a concise overview of relevant aspects in this area. The number of multilingual digital libraries is growing, as is the interest from the research community in these libraries to apply their research findings from cross‐language information retrieval. This review article provides a valuable entry point to the field of multilingual digital libraries for researchers, practitioners, and other interested parties.

This paper aims to understand user information behaviours when they perform multilingual information retrieval. It also offers reference for the development of multilingual information retrieval systems and relevant service platforms.

The authors designed an experiment on multilingual information retrieval with WorldWideScience, utilized Camtasia studio7 (a screen capturing and recording tool) to record overall operational processes of subjects and collected participants’ thought processes with think-aloud protocols. Meanwhile, a questionnaire survey and interviews were used to examine the subjects’ background information, their feelings for the experiment and their ideas about the experimental platform, respectively. Thirty-two valid data points were obtained by 41 subjects.

The users preferred their own language for retrieval. Most users from social science chose general search or advanced search freely according to the tasks. The majority of the participants selected key words directly from the tasks as search terms. Doctoral candidates were more likely to construct a search query with logic symbols. Translation tools were utilized for assisting retrieval and solving doubts of translation. When facing obstacles, users stayed on the original web page to explore continually, followed by back to homepage.

This paper provides a study of user behaviour through investigating how users behave on the whole process of retrieving multilingual information. The findings offer advice for optimizing the function of multilingual information retrieval systems and service platforms.

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.

With an increase in the amount of multilingual content on the World Wide Web, users are often striving to access information provided in a language of which they are non-native speakers. The purpose of this paper is to present a comprehensive study of user profile representation techniques and investigate their use in personalized cross-language information retrieval (CLIR) systems through the means of personalized query expansion.

The user profiles consist of weighted terms computed by using frequency-based methods such as tf-idf and BM25, as well as various latent semantic models trained on monolingual documents and cross-lingual comparable documents. This paper also proposes an automatic evaluation method for comparing various user profile generation techniques and query expansion methods.

Experimental results suggest that latent semantic-weighted user profile representation techniques are superior to frequency-based methods, and are particularly suitable for users with a sufficient amount of historical data. The study also confirmed that user profiles represented by latent semantic models trained on a cross-lingual level gained better performance than the models trained on a monolingual level.

Previous studies on personalized information retrieval systems have primarily investigated user profiles and personalization strategies on a monolingual level. The effect of utilizing such monolingual profiles for personalized CLIR remains unclear. The current study fills the gap by a comprehensive study of user profile representation for personalized CLIR and a novel personalized CLIR evaluation methodology to ensure repeatable and controlled experiments can be conducted.

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 vast amount of multilingual information available online, it becomes increasingly critical for libraries to use various multilingual information access techniques in order to effectively support patrons' online information requests. However, this is still a relatively under‐explored area. This paper aims to study the effectiveness and the adoptability of query expansion and translation enhancement in the context of interactive multilingual information access.

Relying on an interactive multilingual information access system called ICE‐TEA, the authors conducted a controlled experiment (English‐to‐Chinese translation) involving human subjects to assess the retrieval effectiveness, analyzed the collected search logs to examine users' behavior, and employed pre‐ and post‐questionnaires to obtain users' opinions about the system.

The results confirm that significant improvement in retrieval effectiveness can be achieved by combining query expansion with translation enhancement (as compared to a case when there is no relevance feedback). However, users' ability to understand, interact with and even perceive the complex process of searches involving the combination of query expansion and translation enhancement may greatly impact the effectiveness of the techniques. The results also confirm that human‐generated queries were short queries, which calls for careful consideration of how longer queries perform in real search because many search engines rely on longer and more complex queries.

This study examines two important relevance feedback techniques in the context of human‐involved multilingual information access. This study is a valuable addition to the information seeking behaviour literature.

This paper presents a morphological classification of languages from the IR perspective. Linguistic typology research has shown that the morphological complexity of every language in the world can be described by two variables, index of synthesis and index of fusion. These variables provide a theoretical basis for IR research handling morphological issues. A common theoretical framework is needed in particular because of the increasing significance of cross‐language retrieval research and CLIR systems processing different languages. The paper elaborates the linguistic morphological typology for the purposes of IR research. It studies how the indexes of synthesis and fusion could be used as practical tools in mono‐ and cross‐lingual IR research. The need for semantic and syntactic typologies is discussed. The paper also reviews studies made in different languages on the effects of morphology and stemming in IR.

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.