External query reformulation for text-based image retrieval

In text-based image retrieval, the Incomplete Annotation Problem (IAP) can greatly degrade retrieval effectiveness. A standard method used to address this problem is pseudo relevance feedback (PRF) which updates user queries by adding feedback terms selected automatically from top ranked documents in a prior retrieval run. PRF assumes that the target collection provides enough feedback information to select effective expansion terms. This is often not the case in image retrieval since images often only have short metadata annotations leading to the IAP. Our work proposes the use of an external knowledge resource (Wikipedia) in the process of refining user queries. In our method, Wikipedia documents strongly related to the terms in user query (" definition documents") are first identified by title matching between the query and titles of Wikipedia articles. These definition documents are used as indicators to re-weight the feedback documents from an initial search run on a Wikipedia abstract collection using the Jaccard coefficient. The new weights of the feedback documents are combined with the scores rated by different indicators. Query-expansion terms are then selected based on these new weights for the feedback documents. Our method is evaluated on the ImageCLEF WikipediaMM image retrieval task using text-based retrieval on the document metadata fields. The results show significant improvement compared to standard PRF methods

Bayesian variable selection and data integration for biological regulatory networks

A substantial focus of research in molecular biology are gene regulatory networks: the set of transcription factors and target genes which control the involvement of different biological processes in living cells. Previous statistical approaches for identifying gene regulatory networks have used gene expression data, ChIP binding data or promoter sequence data, but each of these resources provides only partial information. We present a Bayesian hierarchical model that integrates all three data types in a principled variable selection framework. The gene expression data are modeled as a function of the unknown gene regulatory network which has an informed prior distribution based upon both ChIP binding and promoter sequence data. We also present a variable weighting methodology for the principled balancing of multiple sources of prior information. We apply our procedure to the discovery of gene regulatory relationships in Saccharomyces cerevisiae (Yeast) for which we can use several external sources of information to validate our results. Our inferred relationships show greater biological relevance on the external validation measures than previous data integration methods. Our model also estimates synergistic and antagonistic interactions between transcription factors, many of which are validated by previous studies. We also evaluate the results from our procedure for the weighting for multiple sources of prior information. Finally, we discuss our methodology in the context of previous approaches to data integration and Bayesian variable selection.Comment: Published in at http://dx.doi.org/10.1214/07-AOAS130 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

New roles for farming in a differentiated countryside: the Portuguese example

Throughout Europe, the role of farming as the private provider of public goods and services increasingly valuated by society is today generally acknowledged. Furthermore, in the turn towards rural development concerns, multifunctionality as an attribute of rural space has emerged, justifying the territorial approach of farming. The situation facing the multifunctionality demand is nevertheless not the same in all European regions, which by all means is getting strengthened in the transition towards post-productivism. In some regions, there is a productivist orientation and production has a dominant economic role, while others will need to be supported on other functions to survive economically and socially, or may be best suited to environmental functions alone. The vocation of the rural territories is different, and thus also the functions they are able to support. This paper discusses the concept of multifunctionality of the rural areas, and defines a possible methodological approach towards the identification of the different types of rural areas in Europe, based on the identification of ideal types, through the analysis of selected indicators. The empirical application has been developed for the Portuguese Ministry of Agriculture, aiming at assessing the differentiated characteristics and dynamics of the Portuguese rural territory. Analyzing data from 1990 and 2000, at municipal level, three dimensions have been considered: the land cover, the agricultural sector and the rural community. Combining the three analyses, it was possible to identify different vocations of the rural space, and the role that farming could have in the future for the multifunctionality of the territory. Accordingly, the municipalities have been grouped in types, pre-defined as ideal types. This was a first attempt to understand the differentiation of the rural territory in Portugal. For decision-making it should be further developed. It nevertheless shows that there is clear differentiation concerning the possible landscape functions to be developed between regions and a possible way to assess. It also shows that a territorial approach to agriculture may be the key for the maintenance of the sector in many areas where production by itself, as it has been know until now, may be severely threatened

Rushes video summarization using a collaborative approach

This paper describes the video summarization system developed by the partners of the K-Space European Network of Excellence for the TRECVID 2008 BBC rushes summarization evaluation. We propose an original method based on individual content segmentation and selection tools in a collaborative system. Our system is organized in several steps. First, we segment the video, secondly we identify relevant and redundant segments, and finally, we select a subset of segments to concatenate and build the final summary with video acceleration incorporated. We analyze the performance of our system through the TRECVID evaluation

Studying Interaction Methodologies in Video Retrieval

So far, several approaches have been studied to bridge the problem of the Semantic Gap, the bottleneck in image and video retrieval. However, no approach is successful enough to increase retrieval performances significantly. One reason is the lack of understanding the user's interest, a major condition towards adapting results to a user. This is partly due to the lack of appropriate interfaces and the missing knowledge of how to interpret user's actions with these interfaces. In this paper, we propose to study the importance of various implicit indicators of relevance. Furthermore, we propose to investigate how this implicit feedback can be combined with static user profiles towards an adaptive video retrieval model

Return to College Education Revisited: Is Relevance Relevant?

This study examines whether the size of the college earnings premium varies depending on the quality of the match between an individual’s degree field and his/her occupation. The study uses the Occupational Information Network (O*NET) to obtain a new measure of the quality of occupational match for a sample of 2268 young adults with post-secondary degrees from the restricted use High School and Beyond (1980/92) data. The study finds that people whose occupations better match their degree fields earn significantly higher returns to post-secondary schooling. This result is robust to controlling for an extensive set of pre-existing differences among individuals, and to accounting for differences in earnings across post-secondary degree fields

Talking to the crowd: What do people react to in online discussions?

This paper addresses the question of how language use affects community reaction to comments in online discussion forums, and the relative importance of the message vs. the messenger. A new comment ranking task is proposed based on community annotated karma in Reddit discussions, which controls for topic and timing of comments. Experimental work with discussion threads from six subreddits shows that the importance of different types of language features varies with the community of interest

A survey on the use of relevance feedback for information access systems

Users of online search engines often find it difficult to express their need for information in the form of a query. However, if the user can identify examples of the kind of documents they require then they can employ a technique known as relevance feedback. Relevance feedback covers a range of techniques intended to improve a user's query and facilitate retrieval of information relevant to a user's information need. In this paper we survey relevance feedback techniques. We study both automatic techniques, in which the system modifies the user's query, and interactive techniques, in which the user has control over query modification. We also consider specific interfaces to relevance feedback systems and characteristics of searchers that can affect the use and success of relevance feedback systems