Search engines

Web search engines are barely ten years old, but they have become familiar and sometimes indispensable tools. Their use has become commonplace in a whole host of everyday life situations, within both professional and private settings (Savolainen, 1995). Planning trips, keeping up with the news, looking for online health information, during key milestones in life, or simply for leisure purposes, individuals are increasingly turning to online resources. Commercial search engines capitalize on t..

User-generated descriptions of individual images versus labels of groups 3 of images: A comparison using basic level theory

Although images are visual information sources with little or no text associated with them, users still tend to use text to describe images and formulate queries. This is because digital libraries and search engines provide mostly text query options and rely on text annotations for representation and retrieval of the semantic content of images. While the main focus of image research is on indexing and retrieval of individual images, the general topic of image browsing and indexing, and retrieval of groups of images has not been adequately investigated. Comparisons of descriptions of individual images as well as labels of groups of images supplied by users using cognitive models are scarce. This work fills this gap. Using the basic level theory as a framework, a comparison of the descriptions of individual images and labels assigned to groups of images by 180 participants in three studies found a marked difference in their level of abstraction. Results confirm assertions by previous researchers in LIS and other fields that groups of images are labeled using more superordinate level terms while individual image descriptions are mainly at the basic level. Implications for design of image browsing interfaces, taxonomies, thesauri, and similar tools are discussed

Community-Contributed Media Collections: Knowledge at Our Fingertips

Abstract The widespread popularity of the Web has supported collaborative efforts to build large collections of community-contributed media. For example, social video-sharing communities like YouTube are incorporating ever-increasing amounts of user-contributed media, or photo-sharing communities like Flickr are managing a huge photographic database at a large scale. The variegated abundance of multimodal, user-generated material opens new and exciting research perspectives and contextually introduces novel challenges. This chapter reviews different collections of user-contributed media, such as YouTube, Flickr, and Wikipedia, by presenting the main features of their online social networking sites. Different research efforts related to community-contributed media collections are presented and discussed. The works described in this chapter aim to (a) improve the automatic understanding of this multimedia data and (b) enhance the document classification task and the user searching activity on media collections

Context-based multimedia semantics modelling and representation

The evolution of the World Wide Web, increase in processing power, and more network bandwidth have contributed to the proliferation of digital multimedia data. Since multimedia data has become a critical resource in many organisations, there is an increasing need to gain efficient access to data, in order to share, extract knowledge, and ultimately use the knowledge to inform business decisions. Existing methods for multimedia semantic understanding are limited to the computable low-level features; which raises the question of how to identify and represent the high-level semantic knowledge in multimedia resources.In order to bridge the semantic gap between multimedia low-level features and high-level human perception, this thesis seeks to identify the possible contextual dimensions in multimedia resources to help in semantic understanding and organisation. This thesis investigates the use of contextual knowledge to organise and represent the semantics of multimedia data aimed at efficient and effective multimedia content-based semantic retrieval.A mixed methods research approach incorporating both Design Science Research and Formal Methods for investigation and evaluation was adopted. A critical review of current approaches for multimedia semantic retrieval was undertaken and various shortcomings identified. The objectives for a solution were defined which led to the design, development, and formalisation of a context-based model for multimedia semantic understanding and organisation. The model relies on the identification of different contextual dimensions in multimedia resources to aggregate meaning and facilitate semantic representation, knowledge sharing and reuse. A prototype system for multimedia annotation, CONMAN was built to demonstrate aspects of the model and validate the research hypothesis, H₁.Towards providing richer and clearer semantic representation of multimedia content, the original contributions of this thesis to Information Science include: (a) a novel framework and formalised model for organising and representing the semantics of heterogeneous visual data; and (b) a novel S-Space model that is aimed at visual information semantic organisation and discovery, and forms the foundations for automatic video semantic understanding

Image Retrieval as Information Seeking Behavior? Self-categorizations of User Motivations to Retrieve Images

The primary goals of this research were to: 1) determine how amateur users of images in web environments self-categorize their interactions with images according to four proposed categories—information seeking, illustrative activity, social activity, or leisure, and; 2) identify which search strategies users rely on to find images online according to motivation.The sample consisted of 28 volunteers drawn from the School of Information Sciences. The study was conducted in a research lab in the University of Pittsburgh's Information Sciences building, where subjects were asked to complete a pre-questionnaire, five tasks using a web browser to locate and view images, and a post-questionnaire. They were also subsequently asked to complete a blog diary of their image retrieval activities over a period of three days. The data collected included pre- and post-questionnaires, video log transcripts, and diary data. The data was analyzed using quantitative analysis, descriptive statistics and probability values. Findings of the study show that: 1) information as a motivation is the overriding reason amateur users engage in image retrieval; 2) the other motivations vary in importance and are not always clearly delineated categories unto themselves, illuminating more about the various contexts of each motivation, and; 3) search strategy is relatively even across motivation. The research indicates that the context of the motivation may be shaped by whether an image is being sought purposefully (information and illustration) or less purposefully (social purposes and leisure) and whether it is being used as data or as an object, especially for information and illustration as motivations and to a lesser degree for social purposes and leisure. A spectrum of search strategy was uncovered ranging from illustration with the most directed, focused search strategy to leisure, the most undirected of motivations in terms of search strategy.A schematic was developed to illustrate the dynamic relationship between the motivations and their contexts. It offers a way of conceiving how the motivations appear on axes of purposeful versus less-than-purposeful image retrieval and data versus object. The schema will make an important contribution by charting what is an otherwise completely unknown area of image retrieval

Étude sur l’influence du vocabulaire utilisé pour l’indexation des images en contexte de repérage multilingue

Depuis quelques années, Internet est devenu un média incontournable pour la diffusion de ressources multilingues. Cependant, les différences linguistiques constituent souvent un obstacle majeur aux échanges de documents scientifiques, culturels, pédagogiques et commerciaux. En plus de cette diversité linguistique, on constate le développement croissant de bases de données et de collections composées de différents types de documents textuels ou multimédias, ce qui complexifie également le processus de repérage documentaire. En général, on considère l’image comme « libre » au point de vue linguistique. Toutefois, l’indexation en vocabulaire contrôlé ou libre (non contrôlé) confère à l’image un statut linguistique au même titre que tout document textuel, ce qui peut avoir une incidence sur le repérage. Le but de notre recherche est de vérifier l’existence de différences entre les caractéristiques de deux approches d’indexation pour les images ordinaires représentant des objets de la vie quotidienne, en vocabulaire contrôlé et en vocabulaire libre, et entre les résultats obtenus au moment de leur repérage. Cette étude suppose que les deux approches d’indexation présentent des caractéristiques communes, mais également des différences pouvant influencer le repérage de l’image. Cette recherche permet de vérifier si l’une ou l’autre de ces approches d’indexation surclasse l’autre, en termes d’efficacité, d’efficience et de satisfaction du chercheur d’images, en contexte de repérage multilingue. Afin d’atteindre le but fixé par cette recherche, deux objectifs spécifiques sont définis : identifier les caractéristiques de chacune des deux approches d’indexation de l’image ordinaire représentant des objets de la vie quotidienne pouvant influencer le repérage, en contexte multilingue et exposer les différences sur le plan de l’efficacité, de l’efficience et de la satisfaction du chercheur d’images à repérer des images ordinaires représentant des objets de la vie quotidienne indexées à l’aide d’approches offrant des caractéristiques variées, en contexte multilingue. Trois modes de collecte des données sont employés : l’analyse des termes utilisés pour l’indexation des images, la simulation du repérage d’un ensemble d’images indexées selon chacune des formes d’indexation à l’étude réalisée auprès de soixante répondants, et le questionnaire administré aux participants pendant et après la simulation du repérage. Quatre mesures sont définies pour cette recherche : l’efficacité du repérage d’images, mesurée par le taux de succès du repérage calculé à l’aide du nombre d’images repérées; l’efficience temporelle, mesurée par le temps, en secondes, utilisé par image repérée; l’efficience humaine, mesurée par l’effort humain, en nombre de requêtes formulées par image repérée et la satisfaction du chercheur d’images, mesurée par son autoévaluation suite à chaque tâche de repérage effectuée. Cette recherche montre que sur le plan de l’indexation de l’image ordinaire représentant des objets de la vie quotidienne, les approches d’indexation étudiées diffèrent fondamentalement l’une de l’autre, sur le plan terminologique, perceptuel et structurel. En outre, l’analyse des caractéristiques des deux approches d’indexation révèle que si la langue d’indexation est modifiée, les caractéristiques varient peu au sein d’une même approche d’indexation. Finalement, cette recherche souligne que les deux approches d’indexation à l’étude offrent une performance de repérage des images ordinaires représentant des objets de la vie quotidienne différente sur le plan de l’efficacité, de l’efficience et de la satisfaction du chercheur d’images, selon l’approche et la langue utilisées pour l’indexation.During the last few years, the Internet has become an indispensable medium for the dissemination of multilingual resources. However, language differences are often a major obstacle to the exchange of scientific, cultural, educational and commercial documents. Besides this linguistic diversity, many databases and collections now contain documents in various formats that can also adversely affect their retrieval process. In general, images are considered to be language-independent resources. Nevertheless, the image indexing process using either a controlled or uncontrolled vocabulary gives the image a linguistic status similar to any other textual document and thus leads to the same difficulties in their retrieval. The goal of our research is to first identify the differences between the indexing approaches using a controlled and an uncontrolled vocabulary for ordinary images of everyday-life objects and to then differentiate between the results obtained at the time of image retrieval. This study supposes that the two indexing approaches show not only common characteristics, but also differences that can influence image retrieval. Thus, this research makes it possible to indicate if one of these indexing approaches surpasses the other in terms of effectiveness, efficiency, and satisfaction of the image searcher in a multilingual retrieval context. For this study, two specific objectives are defined: to identify the characteristics of each approach used for ordinary image indexing of everyday-life objects that can effect image retrieval in a multilingual context; and to explore the differences between the two indexing approaches in terms of their effectiveness, their efficiency, and the satisfaction of the image searcher when trying to retrieve ordinary images of everyday-life objects indexed according to either approach in a multilingual retrieval context. Three methods of data collection are used: an analysis of the image indexing terms, a simulation of the retrieval of a set of images indexed according to each of the two indexing approaches conducted with sixty respondents, and a questionnaire submitted to the participants during and after the retrieval simulation. Four measures are defined in this research: the effectiveness of image retrieval measured by the success rate calculated in terms of the number of retrieved images; time efficiency measured by the average time, in seconds, used to retrieve an image; human efficiency measured in terms of the human effort represented per average number of queries necessary to retrieve an image; and the satisfaction of the image searcher measured by the self-evaluation of the participant of the retrieval process after each completed task. This research shows that in terms of ordinary image indexing representing everyday-life objects, the two approaches investigated are fundamentally distinct on the terminological, perceptual, and structural perspective. Additionally, the analysis of the characteristics of the two indexing approaches reveals that if the indexing language differs, the characteristics vary little within the same indexing approach. Finally, this research underlines that the two indexing approaches of ordinary images representing everyday-life objects have a retrieval performance that is different in terms of its effectiveness, efficiency, and satisfaction of the image searcher according to the approach and the language used for indexing

VideoTag: Encouraging the Effective Tagging of Internet Videos Through Tagging Games

A thesis submitted in partial fulfillment of the requirements of the University of Wolverhampton for the degree of Doctor of PhilosophyAbstract The tags and descriptions entered by video owners in video sharing sites are typically inadequate for retrieval purposes, yet the majority of video search still uses this text. This problem is escalating due to the ease with which users can self-publish videos, generating masses that are poorly labelled and poorly described. This thesis investigates how users tag videos and whether video tagging games can solve this problem by generating useful sets of tags. A preliminary study investigated tags in two social video sharing sites, YouTube and Viddler. YouTube contained many irrelevant tags because the system does not encourage users to tag their videos and does not promote tags as useful. In contrast, using tags as the sole means of categorisation in Viddler motivated users to enter a higher proportion of relevant tags. Poor tags were found in both systems, however, highlighting the need to improve video tagging. In order to give users incentives to tag videos, the VideoTag project in this thesis developed two tagging games, Golden Tag and Top Tag, and one non-game tagging system, Simply Tag, and conducted two experiments with them. In the first experiment VideoTag was a portal to play video tagging games whereas in the second experiment it was a portal to curate collections of special interest videos. Users preferred to tag videos using games, generating tags that were relevant to the videos and that covered a range of tag types that were descriptive of the video content at a predominately specific, objective level. Users were motivated by interest in the content rather than by game elements, and content had an effect on the tag types used. In each experiment, users predominately tagged videos using objective language, with a tendency to use specific rather than basic tags. There was a significant difference between the types of tags entered in the games and in Simply Tag, with more basic, objective vocabulary entered into the games and more specific, objective language entered into the non-game system. Subjective tags were rare but were more frequent in Simply Tag. Gameplay also had an influence on the types of tags entered; Top Tag generated more basic tags and Golden Tag generated more specific and subjective tags. Users were not attracted to use VideoTag by the games alone. Game mechanics had little impact on motivations to use the system. VideoTag used YouTube videos, but could not upload the tags to YouTube and so users could see no benefit for the tags they entered, reducing participation. Specific interest content was more of a motivator for use than games or tagging and that this warrants further research. In the current game-saturated climate, gamification of a video tagging system may therefore be most successful for collections of videos that already have a committed user base.University of Wolverhampto

Web search engine multimedia functionality

Web search engines are beginning to offer access to multimedia searching, including audio, video and image searching. In this paper we report findings from a study examining the state of multimedia search functionality on major general and specialized Web search engines. We investigated 102 Web search engines to examine: (1) how many Web search engines offer multimedia searching, (2) the type of multimedia search functionality and methods offered, such as "query by example", and (3) the supports for personalization or customization which are accessible as advanced search. Findings include: (1) few major Web search engines offer multimedia searching and (2) multimedia Web search functionality is generally limited. Our findings show that despite the increasing level of interest in multimedia Web search, those few Web search engines offering multimedia Web search, provide limited multimedia search functionality. Keywords are still the only means of multimedia retrieval, while other methods such as "query by example" are offered by less than 1% of Web search engines examined