Analysing creative image search information needs.

Creative professionals in advertising, marketing, design and journalism search for images to visually represent a concept for their project. The main purpose of this paper is to present an analysis of documents known as briefs to find search facets, which are widely used in creative industries as a requirements document to describe an information need. The briefs specify the type of image required, such as the content and context of use for the image, and represent the topic from which the searcher builds an image query. This research takes three main sources - user image search behaviour, briefs, search engine meta-data - to examine the search facets for image searching in order to examine the following research question - are meta-data schemes for image search engines sufficient for user needs, or is revision needed? This research found that there are three main classes of user search facet, which include business, contextual and image related information. The key argument in the paper is that the facet 'keyword/tag' is ambiguous and does not support user needs for more generic descriptions to broaden search or specific descriptions to narrow their search - we suggest that a more detailed search facet scheme would be appropriate

Real-time topic detection with bursty n-grams: RGU's submission to the 2014 SNOW challenge.

Twitter is becoming an ever more popular platform for discovering and sharing information about current events, both personal and global. The scale and diversity of messages makes the discovery and analysis of breaking news very challenging. Nonetheless, journalists and other news consumers are increasingly relying on tools to help them make sense of Twitter. Here, we describe a fully-automated system capable of detecting trends related to breaking news in real-time. It identifies words or phrases that `burst' with sudden increased frequencies, and groups these into topics. It identifies a diverse set of recent tweets that are related to these topics, and uses these to create a suitable human-readable headline. In addition, images coming from the diverse tweets are also added to the topic. Our system was evaluated using 24 hours of tweets as part of the Social News On the Web (SNOW) 2014 data challenge

A Context-Sensitive Information System for Mobile Users (Demo)

The abstract is included in the text

Early fusion and query modification in their dual late fusion forms.

In this paper, we prove that specific widely used models in Content-based Image Retrieval for information fusion are interchangeable. In addition, we show that even advanced, non-standard fusion strategies can be represented in dual forms. These models are often classified as representing early or late fusion strategies. We also prove that the standard query modification method with specific similarity measurements can be represented in a late fusion form

Twitter response to televised political debates in Election 2015.

The advent of social media such as Twitter has revolutionised our conversations about live television events. In the days before the Internet, conversation about television programmes was limited to those sitting on the sofa with you and people you met the next morning – so-called ‘water-cooler conversation’. Now, however, it is possible to discuss events on the screen in real time with people all over the country – three out of five UK twitter users tweet while watching television (Nielsen, 2013). Thus it is not surprising to find that the General Election’s television events generated debate and discussion on twitter

On the duality of specific early and late fusion strategies

In this paper, we prove that specific early and specific late fusion strategies are interchangeable. In the case of the late fusion, we consider not only linear but also nonlinear combinations of scores. Our findings are important from both theoretical and practical (applied) perspectives. The duality of specific fusion strategies also answers the question why in the literature the experimental results for both early and late fusion are often similar. The most important aspect of our research is, however, related to the presumable drawbacks of the aforementioned fusion strategies. It is an accepted fact that the main drawback of the early fusion is the curse of dimensionality (generation of high dimensional vectors) whereas the main drawback of the late fusion is its inability to capture correlation between feature spaces. Our proof on the interchangeability of specific fusion schemes undermines this belief. Only one of the possibilities exists: either the late fusion is capable of capturing the correlation between feature spaces or the interaction between the early fusion operators and the similarity measurements decorrelates feature spaces

Event and map content personalisation in a mobile and context-aware environment

Effective methods for information access are of the greatest importance for our modern lives – particularly with respect to handheld devices. Personalisation is one such method which models a user’s characteristics to deliver content more focused to the user’s needs. The emerging area of sophisticated mobile computing devices has started to inspire new forms of personalised systems that include aspects of the person’s contextual environment. This thesis seeks to understand the role of personalisation and context, to evaluate the effectiveness of context for content personalisation and to investigate the event and map content domain for mobile usage. The work presented in this thesis has three parts: The first part is a user experiment on context that investigated the contextual attributes of time, location and interest, with respect to participants’ perception of their usefulness. Results show highly dynamic and interconnected effects of context on participants’ usefulness ratings. In the second part, these results were applied to create a predictive model of context that was related to attribution theory and then combined with an information retrieval score to create a weighted personalisation model. In the third part of this work, the personalisation model was applied in a mobile experiment. Participants solved situational search tasks using a (i) non-personalized and a (ii) personalized mobile information system, and rating entertainment events based on usefulness. Results showed that the personalised system delivered about 20% more useful content to the mobile user than the non-personalised system, with some indication for reduced search effort in terms of time and the amount of queries per task. The work presented provides evidence for the promising potential of context to facilitate personalised information delivery to users of mobile devices. Overall, it serves as an example of an investigation into the effectiveness of context from multiple angles and provides a potential link to some of the aspects of psychology as a potential source for a deeper understanding of contextual processes in humans.EThOS - Electronic Theses Online ServiceSchool of Computing through EU-IST Ambie-Sense projectGBUnited Kingdo