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

Using domain models for context-rich user logging

This paper describes the prototype interactive search sys- Tem being developed within the AutoAdapt project1. The AutoAdapt project seeks to enhance the user experience in searching for information and navigating within selected do- main collections by providing structured representations of domain knowledge to be directly explored, logged, adapted and updated to refject user needs. We propose that this structure is a valuable stepping-stone in context-rich logging of user activities within the information seeking environment. Here we describe the primary components that have been implemented and the user interactions that it will support

Moving towards Adaptive Search

Information retrieval has become very popular over the last decade with the advent of the Web. Nevertheless, searching on the Web is very different to searching on smaller, often more structured collections such as intranets and digital libraries. Such collections are the focus of the recently started AutoAdapt project1. The project seeks to aid user search by providing well-structured domain knowledge to assist query modification and navigation. There are two challenges: acquiring the domain knowledge and adapting it automatically to the specific interest of the user community. At the workshop we will demonstrate an implemented prototype that serves as a starting point on the way to truly adaptive search

Implicit search trails for video recommendation

In this demo paper we demonstrate our approach and system for using implicit actions involved in video search to provide recommendations to users. The goal of this system is to improve the quality of the results that users find, and in doing so, help users to explore a large and difficult information space and help them consider search options that they may not have considered otherwise. Results of a user evaluation show that this approach achieves all of these goals

Collaborative search trails for video search

In this paper we present an approach for supporting users in the difficult task of searching for video. We use collaborative feedback mined from the interactions of earlier users of a video search system to help users in their current search tasks. Our objective is to improve the quality of the results that users find, and in doing so also assist users to explore a large and complex information space. It is hoped that this will lead to them considering search options that they may not have considered otherwise. We performed a user centred evaluation. The results of our evaluation indicate that we achieved our goals, the performance of the users in finding relevant video clips was enhanced with our system; users were able to explore the collection of video clips more and users demonstrated a preference for our system that provided recommendations

Building online employability: a guide for academic departments

This guide will help academic departments to support students to think about their careers and to use the online environment wisely. Used badly the array of social media and online technologies can seriously disadvantage a students’ career development, but if used well they can support students to find out about and transition into their future career.This work was funded by the University of Derby’s Research for Teaching and Learning programme

Use of implicit graph for recommending relevant videos: a simulated evaluation

In this paper, we propose a model for exploiting community based usage information for video retrieval. Implicit usage information from a pool of past users could be a valuable source to address the difficulties caused due to the semantic gap problem. We propose a graph-based implicit feedback model in which all the usage information can be represented. A number of recommendation algorithms were suggested and experimented. A simulated user evaluation is conducted on the TREC VID collection and the results are presented. Analyzing the results we found some common characteristics on the best performing algorithms, which could indicate the best way of exploiting this type of usage information

Main contribution of iconic attractions towards increasing popularity of tourism destinations: an analysis of twitter posts and locations

The social media platforms, due to their universal and comfortable interface, have become the real enablers of a microblogging services. Moreover, with the evolution of online reviews, consumers feel comfortable to express their opinions and share their personal experiences not only about the brands, but also about the travel destinations. Henceforth, social networks such as, Twitter, became important source of information. In this study, author analyzes 4,000 Twitter posts about 2 popular and 2 less popular locations and associated derived sentiments. The study demonstrates that there is a certain difference in perception of locations with a different popularity rank. In terms of information exposure, more popular locations tend to have a higher message diffusion activity, with most of them being of neutral polarity. Additionally, results showed that negative affection is observed more for less popular locations, providing valuable insight for Destination Marketing Organizations. In addition, for both groups, role of followers’ base was ineffective, demonstrating that topic of message sentiment and diffusion are key in tourism domain. Thus, from a methodological point of view, the main contribution of this research is the usage of random and unstructured data in Twitter to the measurement of the perception of the potential visitors of tourist attractions based on the sentiment analysis of posts associated to them. From theoretical point of view, using the sentiment orientation, the study relates to the user exposure and affection of the iconic attractions by the perceived difference in their popularity in accordance with external destination ranking.As redes sociais, devido ao seu interface universal e confortável, tornaram-se reais facilitadores de serviços de microblogging. Por conseguinte, a evolução dos reviews on-line, conferiu aos consumidores maior conforto para expressar as suas opiniões e partilhar as suas experiências pessoais, não apenas sobre as marcas, mas também sobre os seus destinos de viagem. As redes sociais, como o Twitter, tornaram-se importantes fontes de informação. Neste estudo, o autor analisa os sentimentos derivados de 4.000 publicações do Twitter acerca de 2 locais turísticos mais populares e 2 menos populares. O estudo demonstra que há uma certa diferença na percepção dos locais em função do seu grau de popularidade. Em termos de exposição, os locais mais populares tendem a ter uma maior atividade de difusão nas suas mensagens, sendo a maioria delas de polaridade neutra. Adicionalmente, os resultados mostraram que o sentimento negativo é mais partilhado em locais menos populares, fornecendo informações valiosas para Organizações de Marketing. Não obstante, para ambos os grupos, a dimenção da base de seguidores foi irrelevante, demonstrando que o tema da mensagem sentimento e difusão são fundamentais no domínio do turismo. A nível metodológico, o principal contributo desta pesquisa é a análise do sentimento de dados aleatórios e desestruturados do Twitter para a medição da percepção acerca de atracções turísticas com base na. Do ponto de vista teórico, o estudo relaciona-se com a exposição do usuário e o sentimento das atrações icônicas pela diferença percebida na sua popularidade de acordo com um ranking de destinos externo

SOCIAL IMPLICATIONS OF THE INTERNET

The Internet is a critically important research site for sociologists testing theories of technology diffusion and media effects, particularly because it is a medium uniquely capable of integrating modes of communication and forms of content. Current research tends to focus on the Internet’s implications in five domains: 1) inequality (the “digital divide”); 2) community and social capital; 3) political participation; 4) organizations and other economic institutions; and 5) cultural participation and cultural diversity. A recurrent theme across domains is that the Internet tends to complement rather than displace existing media and patterns of behavior. Thus in each domain, utopian claims and dystopic warnings based on extrapolations from technical possibilities have given way to more nuanced and circumscribed understandings of how Internet use adapts to existing patterns, permits certain innovations, and reinforces particular kinds of change. Moreover, in each domain the ultimate social implications of this new technology depend on economic, legal, and policy decisions that are shaping the Internet as it becomes institutionalized. Sociologists need to study the Internet more actively and, particularly, to synthesize research findings on individual user behavior with macroscopic analyses of institutional and political-economic factors that constrain that behavior.World Wide Web, communications, media, technology

Destination image analytics through traveller-generated content

The explosion of content generated by users, in parallel with the spectacular growth of social media and the proliferation of mobile devices, is causing a paradigm shift in research. Surveys or interviews are no longer necessary to obtain users' opinions, because researchers can get this information freely on social media. In the field of tourism, online travel reviews (OTRs) hosted on travel-related websites stand out. The objective of this article is to demonstrate the usefulness of OTRs to analyse the image of a tourist destination. For this, a theoretical and methodological framework is defined, as well as metrics that allow for measuring different aspects (designative, appraisive and prescriptive) of the tourist image. The model is applied to the region of Attica (Greece) through a random sample of 300,000 TripAdvisor OTRs about attractions, activities, restaurants and hotels written in English between 2013 and 2018. The results show trends, preferences, assessments, and opinions from the demand side, which can be useful for destination managers in optimising the distribution of available resources and promoting sustainability