Analysing Web Multimedia Query Reformulation Behaviour

Current multimedia Web search engines still use keywords as the primary means to search. Due to the richness in multimedia contents, general users constantly experience some difficulties in formulating textual queries that are representative enough for their needs. As a result, query reformulation becomes part of an inevitable process in most multimedia searches. Previous Web query formulation studies did not investigate the modification sequences and thus can only report limited findings on the reformulation behavior. In this study, we propose an automatic approach to examine multimedia query reformulation using large-scale transaction logs. The key findings show that search term replacement is the most dominant type of modifications in visual searches but less important in audio searches. Image search users prefer the specified search strategy more than video and audio users. There is also a clear tendency to replace terms with synonyms or associated terms in visual queries. The analysis of the search strategies in different types of multimedia searching provides some insights into user’s searching behavior, which can contribute to the design of future query formulation assistance for keyword-based Web multimedia retrieval systems

Multiple Evidence Combination in Image retrieval: Diogenes Searches for People on the Web

Abstract In this work, we examine evidence combination mechAnisms for classifying multimedia information. In particular, we examine linear and Dempster-Shafer methods of evidence combination in the context of identifying personal images on the World Wide Web. An automatic web search engine named Diogenes 1 searches the web for personal images and combines different pieces of evidence for identification. The sources of evidence consist of input from face detection/recognition and text/HTML analysis modules. A degree of uncertainty is involved with both of these sources. Diogenes automatically determines the uncertainty locally for each retrieval and uses this information to set a relative significance for each evidence. To our knowledge, Diogenes is the first image search engine using Dempster-Shafer evidence combination based on automatic object recognition and dynamic local uncertainty assessment. In our experiments Diogenes comfortably outperformed some well known commercial and research prototype image search engines for celebrity image queries

Investigating people: a qualitative analysis of the search behaviours of open-source intelligence analysts

The Internet and the World Wide Web have become integral parts of the lives of many modern individuals, enabling almost instantaneous communication, sharing and broadcasting of thoughts, feelings and opinions. Much of this information is publicly facing, and as such, it can be utilised in a multitude of online investigations, ranging from employee vetting and credit checking to counter-terrorism and fraud prevention/detection. However, the search needs and behaviours of these investigators are not well documented in the literature. In order to address this gap, an in-depth qualitative study was carried out in cooperation with a leading investigation company. The research contribution is an initial identification of Open-Source Intelligence investigator search behaviours, the procedures and practices that they undertake, along with an overview of the difficulties and challenges that they encounter as part of their domain. This lays the foundation for future research in to the varied domain of Open-Source Intelligence gathering