An Investigation on Text-Based Cross-Language Picture Retrieval Effectiveness through the Analysis of User Queries

Purpose: This paper describes a study of the queries generated from a user experiment for cross-language information retrieval (CLIR) from a historic image archive. Italian speaking users generated 618 queries for a set of known-item search tasks. The queries generated by user’s interaction with the system have been analysed and the results used to suggest recommendations for the future development of cross-language retrieval systems for digital image libraries. Methodology: 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. User’s interactions with the system were recorded and queries were analysed manually quantitatively and qualitatively. Findings: 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 we show the benefits of using high-quality translation resources. The results show the individual characteristics of user’s whilst 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. Limitations and Implications: 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 repository. Value: 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. However, to develop effective systems requires studying user’s search behaviours, particularly in digital image libraries. The value of this paper is in the provision of empirical evidence to support recommendations for effective cross-language image retrieval system design.</p

Multilingual interactive experiments with Flickr

This paper presents a proposal for iCLEF 2006, the interactive track of the CLEF cross-language evaluation campaign. In the past, iCLEF has addressed applications such as information retrieval and question answering. However, for 2006 the focus has turned to text-based image retrieval from Flickr. We describe Flickr, the challenges this kind of collection presents to cross-language researchers, and suggest initial iCLEF tasks

Creating Re-Useable Log Files for Interactive CLIR

This paper discusses the creation of re-useable log files for investigating interactive cross-language search behaviour. This was run as part of iCLEF 2008-09 where the goal was generating a record of user-system interactions based on interactive cross-language image searches. The level of entry to iCLEF was made purposely low with a default search interface and online game environment provided by the organisers. User-system interaction and input from users was recorded in log files for future investigation. This novel approach to running iCLEF resulted in logs containing more than 2 million lines of data

iCLEF 2006 Overview: Searching the Flickr WWW photo-sharing repository

This paper summarizes the task design for iCLEF 2006 (the CLEF interactive track). Compared to previous years, we have proposed a radically new task: searching images in a naturally multilingual database, Flickr, which has millions of photographs shared by people all over the planet, tagged and described in a wide variety of languages. Participants are expected to build a multilingual search front-end to Flickr (using Flickr’s search API) and study the behaviour of the users for a given set of searching tasks. The emphasis is put on studying the process, rather than evaluating its outcome

Neural Embeddings of Graphs in Hyperbolic Space

Neural embeddings have been used with great success in Natural Language Processing (NLP). They provide compact representations that encapsulate word similarity and attain state-of-the-art performance in a range of linguistic tasks. The success of neural embeddings has prompted significant amounts of research into applications in domains other than language. One such domain is graph-structured data, where embeddings of vertices can be learned that encapsulate vertex similarity and improve performance on tasks including edge prediction and vertex labelling. For both NLP and graph based tasks, embeddings have been learned in high-dimensional Euclidean spaces. However, recent work has shown that the appropriate isometric space for embedding complex networks is not the flat Euclidean space, but negatively curved, hyperbolic space. We present a new concept that exploits these recent insights and propose learning neural embeddings of graphs in hyperbolic space. We provide experimental evidence that embedding graphs in their natural geometry significantly improves performance on downstream tasks for several real-world public datasets.Comment: 7 pages, 5 figure

Multimedia retrieval in MultiMatch: The impact of speech transcript errors on search behaviour

This study discusses the findings of an evaluation study on the performance of a multimedia multimodal information access sub-system (MIAS), incorporating automatic speech recognition technology (ASR) to automatically transcribe the speech content of video soundtracks. The study’s results indicate that an information-rich but minimalist graphical interface is preferred. It was also discovered that users tend to have a misplaced confidence in the accuracy of ASR-generated speech transcripts, thus they are not inclined to conduct a systematic auditory inspection (their usual search behaviour) of a video’s soundtrack if the query term does not appear in the transcript. In order to alert the user to the possibility that a search term may be incorrectly recognised as some other word, a matching algorithm is proposed that searches for word sequences of similar phonemic structure to the query term

The Eurovision St Andrews collection of photographs

This report describes the Eurovision image collection compiled for the ImageCLEF (Cross Language Evaluation Forum) evaluation exercise. The image collection consists of around 30,000 photographs from the collection provided by the University of St Andrews Library. The construction and composition of this unique image collection are described, together with the necessary information to obtain and use the image collection

The Performance of MLEM for Dynamic Imaging From Simulated Few-View, Multi-Pinhole SPECT

Stationary small-animal SPECT systems are being developed for rapid dynamic imaging from limited angular views. This work quantified, through simulations, the performance of Maximum Likelihood Expectation Maximization (MLEM) for reconstructing a time-activity curve (TAC) with uptake duration of a few seconds from a stationary, three-camera multi-pinhole SPECT system. The study also quantified the benefits of a heuristic method of initializing the reconstruction with a prior image reconstructed from a conventional number of views, for example from data acquired during the late-study portion of the dynamic TAC. We refer to MLEM reconstruction initialized by a prior-image initial guess (IG) as MLEMig. The effect of the prior-image initial guess on the depiction of contrast between two regions of a static phantom was quantified over a range of angular sampling schemes. A TAC was modeled from the experimentally measured uptake of 99mTc-hexamethylpropyleneamine oxime (HMPAO) in the rat lung. The resulting time series of simulated images was quantitatively analyzed with respect to the accuracy of the estimated exponential washin and washout parameters. In both static and dynamic phantom studies, the prior-image initial guess improved the spatial depiction of the phantom, for example improved definition of the cylinder boundaries and more accurate quantification of relative contrast between cylinders. For example in the dynamic study, there was ~ 50% error in relative contrast for MLEM reconstructions compared to ~ 25-30% error for MLEMig. In the static phantom study, the benefits of the initial guess decreased as the number of views increased. The prior-image initial guess introduced an additive offset in the reconstructed dynamic images, likely due to biases introduced by the prior image. MLEM initialized with a uniform initial guess yielded images that faithfully reproduced the time dependence of the simulated TAC; there were no s- atistically significant differences in the mean exponential washin/washout parameters estimated from MLEM reconstructions compared to the true values. Washout parameters estimated from MLEMig reconstructions did not differ significantly from the true values, however the estimated washin parameter differed significantly from the true value in some cases. Overall, MLEM reconstruction from few views and a uniform initial guess accurately quantified the time dependance of the TAC while introducing errors in the spatial depiction of the object. Initializing the reconstruction with a late-study initial guess improved spatial accuracy while decreasing temporal accuracy in some cases

The Nonprofit Quarterly Study on Nonprofit and Philanthropic Infrastructure

Examines trends in the nonprofit sector's support network and financing system and their capacity to address the impact of the financial crisis on small and midsize nonprofits, share organizational survival strategies, and connect them to resources