163,457 research outputs found

    Exploiting Multi-Evidence from Multiple User's Interests to Personalizing Information Retrieval

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    International audienceThe goal of personalization in information retrieval is to tailor the search engine results to the specific goals, preferences and general interests of the users. We propose a novel model that considers the user's interests as sources of evidence in order to tune the accuracy of documents returned in response to the user query. The model's fundation comes from influence diagrams which are extension of Bayesian graphs, dedicated to decision-making problems. Hence, query evaluation is carried out as an inference process that aims to computing an aggregated utility of a document by considering its relevance to the query but also the corresponding utility with regard to the user's topics of interest. Experimental results using enhanced TREC collections indicate that our personalized retrieval model is effective

    Approaches to implement and evaluate aggregated search

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    La recherche d'information agrĂ©gĂ©e peut ĂȘtre vue comme un troisiĂšme paradigme de recherche d'information aprĂšs la recherche d'information ordonnĂ©e (ranked retrieval) et la recherche d'information boolĂ©enne (boolean retrieval). Les deux paradigmes les plus explorĂ©s jusqu'Ă  aujourd'hui retournent un ensemble ou une liste ordonnĂ©e de rĂ©sultats. C'est Ă  l'usager de parcourir ces ensembles/listes et d'en extraire l'information nĂ©cessaire qui peut se retrouver dans plusieurs documents. De maniĂšre alternative, la recherche d'information agrĂ©gĂ©e ne s'intĂ©resse pas seulement Ă  l'identification des granules (nuggets) d'information pertinents, mais aussi Ă  l'assemblage d'une rĂ©ponse agrĂ©gĂ©e contenant plusieurs Ă©lĂ©ments. Dans nos travaux, nous analysons les travaux liĂ©s Ă  la recherche d'information agrĂ©gĂ©e selon un schĂ©ma gĂ©nĂ©ral qui comprend 3 parties: dispatching de la requĂȘte, recherche de granules d'information et agrĂ©gation du rĂ©sultat. Les approches existantes sont groupĂ©es autours de plusieurs perspectives gĂ©nĂ©rales telle que la recherche relationnelle, la recherche fĂ©dĂ©rĂ©e, la gĂ©nĂ©ration automatique de texte, etc. Ensuite, nous nous sommes focalisĂ©s sur deux pistes de recherche selon nous les plus prometteuses: (i) la recherche agrĂ©gĂ©e relationnelle et (ii) la recherche agrĂ©gĂ©e inter-verticale. * La recherche agrĂ©gĂ©e relationnelle s'intĂ©resse aux relations entre les granules d'information pertinents qui servent Ă  assembler la rĂ©ponse agrĂ©gĂ©e. En particulier, nous nous sommes intĂ©ressĂ©s Ă  trois types de requĂȘtes notamment: requĂȘte attribut (ex. prĂ©sident de la France, PIB de l'Italie, maire de Glasgow, ...), requĂȘte instance (ex. France, Italie, Glasgow, Nokia e72, ...) et requĂȘte classe (pays, ville française, portable Nokia, ...). Pour ces requĂȘtes qu'on appelle requĂȘtes relationnelles nous avons proposĂ©s trois approches pour permettre la recherche de relations et l'assemblage des rĂ©sultats. Nous avons d'abord mis l'accent sur la recherche d'attributs qui peut aider Ă  rĂ©pondre aux trois types de requĂȘtes. Nous proposons une approche Ă  large Ă©chelle capable de rĂ©pondre Ă  des nombreuses requĂȘtes indĂ©pendamment de la classe d'appartenance. Cette approche permet l'extraction des attributs Ă  partir des tables HTML en tenant compte de la qualitĂ© des tables et de la pertinence des attributs. Les diffĂ©rentes Ă©valuations de performances effectuĂ©es prouvent son efficacitĂ© qui dĂ©passe les mĂ©thodes de l'Ă©tat de l'art. DeuxiĂšmement, nous avons traitĂ© l'agrĂ©gation des rĂ©sultats composĂ©s d'instances et d'attributs. Ce problĂšme est intĂ©ressant pour rĂ©pondre Ă  des requĂȘtes de type classe avec une table contenant des instances (lignes) et des attributs (colonnes). Pour garantir la qualitĂ© du rĂ©sultat, nous proposons des pondĂ©rations sur les instances et les attributs promouvant ainsi les plus reprĂ©sentatifs. Le troisiĂšme problĂšme traitĂ© concerne les instances de la mĂȘme classe (ex. France, Italie, Allemagne, ...). Nous proposons une approche capable d'identifier massivement ces instances en exploitant les listes HTML. Toutes les approches proposĂ©es fonctionnent Ă  l'Ă©chelle Web et sont importantes et complĂ©mentaires pour la recherche agrĂ©gĂ©e relationnelle. Enfin, nous proposons 4 prototypes d'application de recherche agrĂ©gĂ©e relationnelle. Ces derniers peuvent rĂ©pondre des types de requĂȘtes diffĂ©rents avec des rĂ©sultats relationnels. Plus prĂ©cisĂ©ment, ils recherchent et assemblent des attributs, des instances, mais aussi des passages et des images dans des rĂ©sultats agrĂ©gĂ©s. Un exemple est la requĂȘte ``Nokia e72" dont la rĂ©ponse sera composĂ©e d'attributs (ex. prix, poids, autonomie batterie, ...), de passages (ex. description, reviews, ...) et d'images. Les rĂ©sultats sont encourageants et illustrent l'utilitĂ© de la recherche agrĂ©gĂ©e relationnelle. * La recherche agrĂ©gĂ©e inter-verticale s'appuie sur plusieurs moteurs de recherche dits verticaux tel que la recherche d'image, recherche vidĂ©o, recherche Web traditionnelle, etc. Son but principal est d'assembler des rĂ©sultats provenant de toutes ces sources dans une mĂȘme interface pour rĂ©pondre aux besoins des utilisateurs. Les moteurs de recherche majeurs et la communautĂ© scientifique nous offrent dĂ©jĂ  une sĂ©rie d'approches. Notre contribution consiste en une Ă©tude sur l'Ă©valuation et les avantages de ce paradigme. Plus prĂ©cisĂ©ment, nous comparons 4 types d'Ă©tudes qui simulent des situations de recherche sur un total de 100 requĂȘtes et 9 sources diffĂ©rentes. Avec cette Ă©tude, nous avons identifiĂ©s clairement des avantages de la recherche agrĂ©gĂ©e inter-verticale et nous avons pu dĂ©duire de nombreux enjeux sur son Ă©valuation. En particulier, l'Ă©valuation traditionnelle utilisĂ©e en RI, certes la moins rapide, reste la plus rĂ©aliste. Pour conclure, nous avons proposĂ© des diffĂ©rents approches et Ă©tudes sur deux pistes prometteuses de recherche dans le cadre de la recherche d'information agrĂ©gĂ©e. D'une cĂŽtĂ©, nous avons traitĂ© trois problĂšmes importants de la recherche agrĂ©gĂ©e relationnelle qui ont portĂ© Ă  la construction de 4 prototypes d'application avec des rĂ©sultats encourageants. De l'autre cĂŽtĂ©, nous avons mis en place 4 Ă©tudes sur l'intĂ©rĂȘt et l'Ă©valuation de la recherche agrĂ©gĂ©e inter-verticale qui ont permis d'identifier les enjeux d'Ă©valuation et les avantages du paradigme. Comme suite Ă  long terme de ce travail, nous pouvons envisager une recherche d'information qui intĂšgre plus de granules relationnels et plus de multimĂ©dia.Aggregated search or aggregated retrieval can be seen as a third paradigm for information retrieval following the Boolean retrieval paradigm and the ranked retrieval paradigm. In the first two, we are returned respectively sets and ranked lists of search results. It is up to the time-poor user to scroll this set/list, scan within different documents and assemble his/her information need. Alternatively, aggregated search not only aims the identification of relevant information nuggets, but also the assembly of these nuggets into a coherent answer. In this work, we present at first an analysis of related work to aggregated search which is analyzed with a general framework composed of three steps: query dispatching, nugget retrieval and result aggregation. Existing work is listed aside different related domains such as relational search, federated search, question answering, natural language generation, etc. Within the possible research directions, we have then focused on two directions we believe promise the most namely: relational aggregated search and cross-vertical aggregated search. * Relational aggregated search targets relevant information, but also relations between relevant information nuggets which are to be used to assemble reasonably the final answer. In particular, there are three types of queries which would easily benefit from this paradigm: attribute queries (e.g. president of France, GDP of Italy, major of Glasgow, ...), instance queries (e.g. France, Italy, Glasgow, Nokia e72, ...) and class queries (countries, French cities, Nokia mobile phones, ...). We call these queries as relational queries and we tackle with three important problems concerning the information retrieval and aggregation for these types of queries. First, we propose an attribute retrieval approach after arguing that attribute retrieval is one of the crucial problems to be solved. Our approach relies on the HTML tables in the Web. It is capable to identify useful and relevant tables which are used to extract relevant attributes for whatever queries. The different experimental results show that our approach is effective, it can answer many queries with high coverage and it outperforms state of the art techniques. Second, we deal with result aggregation where we are given relevant instances and attributes for a given query. The problem is particularly interesting for class queries where the final answer will be a table with many instances and attributes. To guarantee the quality of the aggregated result, we propose the use of different weights on instances and attributes to promote the most representative and important ones. The third problem we deal with concerns instances of the same class (e.g. France, Germany, Italy ... are all instances of the same class). Here, we propose an approach that can massively extract instances of the same class from HTML lists in the Web. All proposed approaches are applicable at Web-scale and they can play an important role for relational aggregated search. Finally, we propose 4 different prototype applications for relational aggregated search. They can answer different types of queries with relevant and relational information. Precisely, we not only retrieve attributes and their values, but also passages and images which are assembled into a final focused answer. An example is the query ``Nokia e72" which will be answered with attributes (e.g. price, weight, battery life ...), passages (e.g. description, reviews ...) and images. Results are encouraging and they illustrate the utility of relational aggregated search. * The second research direction that we pursued concerns cross-vertical aggregated search, which consists of assembling results from different vertical search engines (e.g. image search, video search, traditional Web search, ...) into one single interface. Here, different approaches exist in both research and industry. Our contribution concerns mostly evaluation and the interest (advantages) of this paradigm. We propose 4 different studies which simulate different search situations. Each study is tested with 100 different queries and 9 vertical sources. Here, we could clearly identify new advantages of this paradigm and we could identify different issues with evaluation setups. In particular, we observe that traditional information retrieval evaluation is not the fastest but it remains the most realistic. To conclude, we propose different studies with respect to two promising research directions. On one hand, we deal with three important problems of relational aggregated search following with real prototype applications with encouraging results. On the other hand, we have investigated on the interest and evaluation of cross-vertical aggregated search. Here, we could clearly identify some of the advantages and evaluation issues. In a long term perspective, we foresee a possible combination of these two kinds of approaches to provide relational and cross-vertical information retrieval incorporating more focus, structure and multimedia in search results

    Soft peer review: social software and distributed scientific evaluation

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    The debate on the prospects of peer-review in the Internet age and the increasing criticism leveled against the dominant role of impact factor indicators are calling for new measurable criteria to assess scientific quality. Usage-based metrics offer a new avenue to scientific quality assessment but face the same risks as first generation search engines that used unreliable metrics (such as raw traffic data) to estimate content quality. In this article I analyze the contribution that social bookmarking systems can provide to the problem of usage-based metrics for scientific evaluation. I suggest that collaboratively aggregated metadata may help fill the gap between traditional citation-based criteria and raw usage factors. I submit that bottom-up, distributed evaluation models such as those afforded by social bookmarking will challenge more traditional quality assessment models in terms of coverage, efficiency and scalability. Services aggregating user-related quality indicators for online scientific content will come to occupy a key function in the scholarly communication system

    Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach

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    We systematically investigate the effect heterogeneity of job search programmes for unemployed workers. To investigate possibly heterogeneous employment effects, we combine non-experimental causal empirical models with Lasso-type estimators. The empirical analyses are based on rich administrative data from Swiss social security records. We find considerable heterogeneities only during the first six months after the start of training. Consistent with previous results of the literature, unemployed persons with fewer employment opportunities profit more from participating in these programmes. Furthermore, we also document heterogeneous employment effects by residence status. Finally, we show the potential of easy-to-implement programme participation rules for improving average employment effects of these active labour market programmes

    Peer to Peer Information Retrieval: An Overview

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    Peer-to-peer technology is widely used for file sharing. In the past decade a number of prototype peer-to-peer information retrieval systems have been developed. Unfortunately, none of these have seen widespread real- world adoption and thus, in contrast with file sharing, information retrieval is still dominated by centralised solutions. In this paper we provide an overview of the key challenges for peer-to-peer information retrieval and the work done so far. We want to stimulate and inspire further research to overcome these challenges. This will open the door to the development and large-scale deployment of real-world peer-to-peer information retrieval systems that rival existing centralised client-server solutions in terms of scalability, performance, user satisfaction and freedom

    Consumers’ Demand for Pork Quality: Applying Semantic Network Analysis, May 2006

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    Abstract Consideration of consumers’ demand for food quality entails several aspects. Quality itself is a complex and dynamic concept, and constantly evolving technical progress may cause changes in consumers’ judgment of quality. To improve our understanding of the factors influencing the demand for quality, food quality must be defined and measured from the consumer’s perspective (Cardello, 1995). The present analysis addresses the issue of food quality, focusing on pork—the food that respondents were concerned about. To gain insight into consumers’ demand, we analyzed their perception and evaluation and focused on their cognitive structures concerning pork quality. In order to more fully account for consumers’ concerns about the origin of pork, in 2004 we conducted a consumer survey of private households. The qualitative approach of concept mapping was used to uncover the cognitive structures. Network analysis was applied to interpret the results. In order to make recommendations to enterprises, we needed to know what kind of demand emerges from the given food quality schema. By establishing the importance and relative positions of the attributes, we find that the country of origin and butcher may be the two factors that have the biggest influence on consumers’ decisions about the purchase of pork

    A personalized and context-aware news offer for mobile devices

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    For classical domains, such as movies, recommender systems have proven their usefulness. But recommending news is more challenging due to the short life span of news content and the demand for up-to-date recommendations. This paper presents a news recommendation service with a content-based algorithm that uses features of a search engine for content processing and indexing, and a collaborative filtering algorithm for serendipity. The extension towards a context-aware algorithm is made to assess the information value of context in a mobile environment through a user study. Analyzing interaction behavior and feedback of users on three recommendation approaches shows that interaction with the content is crucial input for user modeling. Context-aware recommendations using time and device type as context data outperform traditional recommendations with an accuracy gain dependent on the contextual situation. These findings demonstrate that the user experience of news services can be improved by a personalized context-aware news offer

    Measures to eradicate multidrug-resistant organism outbreaks: How much does it cost?

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    This study aimed to assess the economic burden of infection control measures that succeeded in eradicating multidrug-resistant organisms (MDROs) in emerging epidemic contexts in hospital settings. The MEDLINE, EMBASE and Ovid databases were systematically interrogated for original English-language articles detailing costs associated with strict measures to eradicate MDROs published between 1 January 1974 and 2 November 2014. This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Overall, 13 original articles were retrieved reporting data on several MDROs, including glycopeptide-resistant enterococci (n = 5), carbapenemase-producing Enterobacteriacae (n = 1), methicillin-resistant Staphylococcus aureus (n = 5), and carbapenem-resistant Acinetobacter baumannii (n = 2). Overall, the cost of strict measures to eradicate MDROs ranged from €285 to €57 532 per positive patient. The major component of these overall costs was related to interruption of new admissions, representing €2466 to €47 093 per positive patient (69% of the overall mean cost; range, 13-100%), followed by mean laboratory costs of €628 to €5849 (24%; range, 3.3-56.7%), staff reinforcement costs of €6204 to €148 381 (22%; range, 3.3-52%), and contact precautions costs of €166 to €10 438 per positive patient (18%; range, 0.7-43.3%). Published data on the economic burden of strict measures to eradicate MDROs are limited, heterogeneous, and weakened by several methodological flaws. Novel economic studies should be performed to assess the financial impact of current policies, and to identify the most cost-effective strategies to eradicate emerging MDROs in healthcare facilities
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