Miguel E. Ruiz

Improving query expansion for image retrieval via saliency and picturability

In this paper, we present a Wikipedia-based approach to query expansion for the task of image retrieval, by combining salient encyclopaedic concepts with the picturability of words. Our model generates the expanded query terms in a definite two-stage process instead of multiple iterative passes, requires no manual feedback, and is completely unsupervised. Preliminary results show that our proposed model is effective in a comparative study on the ImageCLEF 2010 Wikipedia dataset.

Users' image seeking behavior in a multilingual tag environment

This paper presents the results of a user study conducted in the framework of the Interactive Image Retrieval task at CLEF 2009. The main goal of our research is to understand the way in which users search for images that have been annotated with multilingual tags. The study is based on the application of grounded theory to try to understand the challenges that users face when searching for images that have multilingual annotations, and how they cope with these challenges to find the information they need. The study includes two methods of data collection: an online survey and a face to face interview that included a search task using Flickling. Because this was our first year participating in the interactive image CLEF, we found that the most challenging aspect of conducting a user centered evaluation in the context of CLEF is the short amount of time that is available from the time the task is defined and the deadline for submitting results. We were able to conduct face to face interviews for approximately three weeks (from 6/29/2009 to 7/17/2009) before the Flickling system was shut down. Our online survey was also made available at the end of June and we report here the results that we have collected until the end of November 2009. During this time we collected 27 responses to the online questionnaire and 6 face to face interviews. Our results indicate that 67% of the users search for images at least once a week and that the most common purposes for finding images are entertainment and professional. Our results from the user interviews indicate that the users find the known-item retrieval task hard to do due to the difficulty in expressing the contents of the target image using tags that could have also been assigned by the creator of the image. The face to face interviews also give some feedback for improving the current Flickling interface, particularly the addition of a spell checking mechanism and the improvement of the multilingual translation of terms selected by users.

Adoption and evaluation issues of automatic and computer aided indexing systems

This panel will present an overview of the state-of-the-art in automatic and computer aided indexing systems, and focus on discussion of the factors that influence the success of the implementation of these system as well as the criteria for evaluation. We also will present several case studies of operational systems such as the Indexing Initiative at the National Library of Medicine, the American Water Works Association, the IEEE and ASIS&T Digital Library. Final recommendations and “best practices” will be presented and discussed among panel members and the audience.

Digital libraries for biodiversity and natural history collections

This panel aims to discuss the importance of creating digital libraries for biodiversity and natural history collections, the state of the art in terms of standards, best practices and the challenges that natural history museums and herbaria face when trying to digitize their collections, and the creation and management of personal digital libraries for botanical learning.

Evaluation of Automatically Assigned MeSH Terms for Retrieval of Medical Images

This paper presents the results of the State University of New York at Buffalo (UB) team in collaboration with the National Library of Medicine (NLM) in the 2007 ImageCLEFmed task. We use a system that combines visual features (using a CBIR System) and text retrieval. We used the Medical Text Indexer (MTI) developed by NLM to automatically assign MeSH terms and UMLS concepts to the English free text annotations of the images. We also used an equivalent system called MAIF that automatically assigns MeSH and UMLS concepts to French free text. Our results indicate that the use of automatically assigned UMLS concepts improves retrieval performance significantly. We also identified specific aspects of the system that could be improved in the future, such as the method used to perform the automatic translation of medical terms and the addition of image classification to process queries targeted to a specific image modality.

HeMT: A Multilingual System for Human Evaluation of Metadata Records Machine Translation

We demonstrate HeMT, a multilingual Web system for human evaluation of machine translated metadata records. It allows human evaluators to examine and assess machine translation results for sample metadata records in Chinese, English, and Spanish. This paper describes the design principles, users, and the functions of the system. It also presents the research design of a small-scale usability testing that will not only examine the appearance of the Website, but also the accuracy of the content and the Website’s cultural appropriateness.

Users' seeking behavior and multilingual image tags

Sharing and tagging images is an activity that is very popular among web users. This has lead to the creation of Internet services such as Flickr that allow users to post their own pictures and tag them with the purpose of sharing them with friends and displaying their work in a public forum. This poster presents the results of a study conducted in the framework of the Interactive Image Retrieval (iCLEF) task, which is part of the Cross Language Evaluation Forum (CLEF). The main goal of the study is to identify the challenges that users face when they search for images annotated in languages other than English. Our results indicate that the users find the task to be very hard due to the difficulty of selecting terms that match those assigned by the creators of the images. The results also suggest that the increasingly popular tagging of images has limitations similar to those encountered with controlled vocabularies, specifically vocabulary mismatch among searchers and creators of content.

The libraries of Second Life: How MUVE could shape the future of digital libraries

This panel will present an overview of Multi User Virtual Environments (MUVE), specifically Second Life (SL), and its applications in library services and education. The panel includes practitioners as well as educators that have been developing applications in Second Life. They will be presenting current applications of SL in Libraries and virtual campuses, and discuss usability issues associated to these environments.