Personalized Image Search Using Complex Multiple Words Based Queries

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Gossiping Personalized Queries

International audienceThis paper presents P3Q, a fully decentralized gossip-based protocol to personalize query processing in social tagging systems. P3Q dynamically associates each user with social acquaintances sharing similar tagging behaviours. Queries are gossiped among such acquaintances, computed on the fly in a collaborative, yet partitioned manner, and results are iteratively refined and returned to the querier. Analytical and experimental evaluations convey the scalability of P3Q for top-k query processing. More specifically, we show that on a 10,000-user delicious trace, with little storage at each user, the queries are accurately computed within reasonable time and bandwidth consumption. We also report on the inherent ability of P3Q to cope with users updating profiles and departing

Usagers & Recherche d'Information

La recherche d'information est confrontée à une variété de plus en plus importante tant en termes d'usagers, de tâches à remplir, d'outils.... Face à cette hétérogénéité de nombreux travaux, s'attachent à améliorer la recherche d'information par le biais d'approches adaptatives, de systèmes de recommandation... Mes travaux s'inscrivent dans ce cadre et apportent un éclairage essentiellement porté sur l'usager et ses activités et plus particulièrement sur la recherche d'information. Les résultats correspondent à 3 angles d'investigation nous permettant d'aborder cette problématique de l'hétérogénéité en Recherche d'Information

Recherche d'information et contexte

My research work is related the field of Information Retrieval (IR) whose objective is to enable a user to find information that meets its needs within a large volume of information. The work in IR have focused primarily on improving information processing in terms of indexing to obtain optimal representations of documents and queries and in terms of matching between these representations. Contributions have long made no distinction between all searches assuming a unique type of search and when proposing a model intended to be effective for this unique type of search. The growing volume of information and diversity of situations have marked the limits of existing IR approaches bringing out the field of contextual IR. Contextual IR aims to better respond to users' needs taking into account the search context. The principle is to differentiate searches by integrating in the IR process, contextual factors that will influence the IRS effectiveness. The notion of context is broad and refers to all knowledge related to information conducted by a user querying an IRS. My research has been directed toward taking into account the contextual factors that are: the domain of information, the information structure and the user. The first three directions of my work consist in proposing models that incorporate each of these elements of context, and a fourth direction aims at exploring how to adapt the process to each search according to its context. Various European and national projects have provided application frameworks for this research and have allowed us to validate our proposals. This research has also led to development of various prototypes and allowed the conduct of PhD theses and research internships.Mes travaux de recherche s'inscrivent dans le domaine de la recherche d'information (RI) dont l'objectif est de permettre à un utilisateur de trouver de l'information répondant à son besoin au sein d'un volume important d'informations. Les recherches en RI ont été tout d'abord orientées système. Elles sont restées très longtemps axées sur l'appariement pour évaluer la correspondance entre les requêtes et les documents ainsi que sur l'indexation des documents et de requêtes pour obtenir une représentation qui supporte leur mise en correspondance. Cela a conduit à la définition de modèles théoriques de RI comme le modèle vectoriel ou le modèle probabiliste. L'objectif initialement visé a été de proposer un modèle de RI qui possède un comportement global le plus efficace possible. La RI s'est longtemps basée sur des hypothèses simplificatrices notamment en considérant un type unique d'interrogation et en appliquant le même traitement à chaque interrogation. Le contexte dans lequel s'effectue la recherche a été ignoré. Le champ d'application de la RI n'a cessé de s'étendre notamment grâce à l'essor d'internet. Le volume d'information toujours plus important combiné à une utilisation de SRI qui s'est démocratisée ont conduit à une diversité des situations. Cet essor a rendu plus difficile l'identification des informations correspondant à chaque besoin exprimé par un utilisateur, marquant ainsi les limites des approches de RI existantes. Face à ce constat, des propositions ont émergé, visant à faire évoluer la RI en rapprochant l'utilisateur du système tels que les notions de réinjection de pertinence utilisateur ou de profil utilisateur. Dans le but de fédérer les travaux et proposer des SRI offrant plus de précision en réponse au besoin de l'utilisateur, le domaine de la RI contextuelle a récemment émergé. L'objectif est de différencier les recherches au niveau des modèles de RI en intégrant des éléments de contexte susceptibles d'avoir une influence sur les performances du SRI. La notion de contexte est vaste et se réfère à toute connaissance liée à la recherche de l'utilisateur interrogeant un SRI. Mes travaux de recherche se sont orientés vers la prise en compte des éléments de contexte que sont le domaine de l'information, la structure de l'information et l'utilisateur. Ils consistent, dans le cadre de trois premières orientations, à proposer des modèles qui intègrent chacun de ces éléments de contexte, et, dans une quatrième orientation, d'étudier comment adapter les processus à chaque recherche en fonction de son contexte. Différents projets européens et nationaux ont servi de cadre applicatifs à ces recherches et ainsi à valider nos propositions. Mes travaux de recherche ont également fait l'objet de développements dans différents prototypes et ont permis le déroulement de thèses de doctorat et stages de recherche

The Use of Social Tags in Text and Image Searching on the Web.

In recent years, tags have become a standard feature on a diverse range of sites on the Web, accompanying blog posts, photos, videos, and online news stories. Tags are descriptive terms attached to Internet resources. Despite the rapid adoption of tagging, how people use tags during the search process is not well understood. There is little empirical data on the use and perceptions of tags created by those other than the searcher. Previous research on tags focused on the motivations and behaviors of taggers, although non-taggers represent a larger proportion of Web users than taggers. This study examines how people use tags, created by others, during the search process. Forty-eight subjects were each assigned four search tasks in a within-subjects study. Subjects searched for text documents and images in a controlled laboratory setting, using information retrieval interfaces differing in their incorporation of tags. User behavior and perception data were collected through search logs and interviews. Both direct and indirect uses of tags across the search process were examined. Tags are used directly when they are clicked on, resulting in a new query, while tags are used indirectly when used for judgments of relevance or to obtain additional terms for query reformulation. Tags increased interactions with the information retrieval system, as subjects issued more queries and saw more search results when using the tagged interface. For both text and image searches, tags were used for query reformulation, predictive judgment, and evaluative judgment of relevance. Subjects interacted most frequently with tags on the search results page, using them for query reformulation and predictive judgment. Tags were more likely to be used for predictive judgment in text searches than in image searches. Subjects’ understanding of tags focused on the role of tags in search, especially findability through a search engine. Tags were not uniformly perceived as being user-generated; site owners and automatic generation were mentioned as sources of tags. Several implications for the design of search interfaces and presentation of tags to support information interactions are discussed in the conclusion.Ph.D.InformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/89816/1/kimym_1.pd

Tag data and personalized information retrieval

Researchers investigating personalization techniques for Web Information Retrieval face a challenge; that the data required to perform evaluations, namely query logs and clickthrough data, is not readily available due to valid privacy concerns. One option for researchers is to perform a user study, however, such experiments are often limited to small (and sometimes biased) samples of users, restricting somewhat the conclusions that can be drawn. Alternatively, researchers can look for publicly available data that can be used to approximate query logs and click-through data. Recently it has been shown that the information contained in social bookmarking (tagging) systems may be useful for improving Web search. We investigate the use of tag data for evaluating personalized retrieval systems involving thousands of users. Using data from the social bookmarking site del.icio.us, we demonstrate how one can rate the quality of personalized retrieval results. Furthermore, we conduct experiments involving various smoothing techniques and profile settings, which show that a user’s “bookmark history ” can be used to improve search results via personalization. Analogously to studies involving implicit feedback mechanisms in IR, which have found that profiles based on the content of clicked URLs outperform those based on past queries alone, we find that profiles based on the content of bookmarked URLs are generally superior to those based on tags alone