Diversity, Assortment, Dissimilarity, Variety: A Study of Diversity Measures Using Low Level Features for Video Retrieval

In this paper we present a number of methods for re-ranking video search results in order to introduce diversity into the set of search results. The usefulness of these approaches is evaluated in comparison with similarity based measures, for the TRECVID 2007 collection and tasks [11]. For the MAP of the search results we find that some of our approaches perform as well as similarity based methods. We also find that some of these results can improve the P@N values for some of the lower N values. The most successful of these approaches was then implemented in an interactive search system for the TRECVID 2008 interactive search tasks. The responses from the users indicate that they find the more diverse search results extremely useful

The National Transport Data Framework

Report by Professor Peter Landshoff (Cambridge University) and Professor John Polak (Imperial College London) on a project for the Department for Transport. emails: [email protected] [email protected] NTDF is designed to be a resource for data owners to deposit descriptions into a central catalogue, so that people can search for data and find data and understand their characteristics. The value of this is to individuals, to commercial organizations, and to public bodies. For example, services that provide better information to travellers will help to make their journey less stressful and persuade them to make more use of public transport. Transport operators need very diverse information to help them plan developments to their services: demographic, geographical, economic etc. And policy makers need a similar range of information to help them decide how to divide their budget and afterwards to evaluate how valuable it has been.This work was supported by the Department for Transport (DfT)

Data Management Challenges for Internet-scale 3D Search Engines

This paper describes the most significant data-related challenges involved in building internet-scale 3D search engines. The discussion centers on the most pressing data management issues in this domain, including model acquisition, support for multiple file formats, asset versioning, data integrity errors, the data lifecycle, intellectual property, and the legality of web crawling. The paper also discusses numerous issues that fall under the rubric of trustworthy computing, including privacy, security, inappropriate content, and copying/remixing of assets. The goal of the paper is to provide an overview of these general issues, illustrated by empirical data drawn from the internet's largest operational search engine. While numerous works have been published on 3D information retrieval, this paper is the first to discuss the real-world challenges that arise in building practical search engines at scale.Comment: Second version, distributed by SIGIR Foru

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