Des offres de location de biens en partage fleurissent dans les villes : Vélib’, Autolib’, l’autopartage.... Louer l’usage suppose de partager l’utilisation du bien à plusieurs et d’accepter de se dégager de la matérialité au profit de la fonctionnalité. C’est aussi un argument en faveur d’une consommation plus écoresponsable. Louer l’usage d’un bien en partage ou l’acheter, qu’en pense le consommateur ? La valeur réside dans les bénéfices qu'il retire de l’utilisation, et non de la possession. C’est également une nouvelle expérience chargée de sens ; elle est acceptée, bricolée, refusée ou réinterprétée par les consommateurs. Selon les principes de la Grounded Theory, un recueil de données grâce à des récits de vie nous éclaire sur l’attrait de cette offre de service ; et, au travers des formes prises par le discours, ce sont les valeurs, les idéaux et les attitudes des acheteurs qui émergent. Puis, nous tentons de déterminer les antécédents de la prise de décision de louer l’usage dans le cas de biens en partage, et de présenter une typologie de logiques de consommation de l’usage. Nous tenons à voir l’intérêt managérial d’une stratégie de différenciation expérientielle conjuguée à un positionnement écocitoyen pour distribuer la location de l’usage / Offers of sharing services are springing up in cities: Vélib’, Autolib’, carsharing.... Using up involves sharing the service with multiple users and agreeing to separate oneself from all materialism in favor of functionality. This is also an argument towards a more responsible consumption. Hiring or buying, what does the consumer think about it? The value lies in the benefits of use rather than in its possession. It is also a new meaningful experience accepted, tinkered, refused or reinterpreted by the consumers. According to the Grounded Theory principles, a data collection based on life stories, it provides us new information on the attractiveness of this offer of service; and according to the forms taken by the discourse, what emerge are the values, ideals and attitudes of buyers. We try to determine the history of the decision of hiring the use and to propose a typology of the logical specific universe of consuming the use. And then, we want then to put on light on the managerial interest of a strategy of differentiation based on experience combined with an eco-citizen positioning to distribute the location of the use

Pas de résumé en français / No summary

The diploma thesis focuses on the mechanisms set up campaigns in ppc systems. Thesis discusses the role of PPC in the marketing mix of the company, compares ppc with other similar tools (e.g. SEO). The practical part describes the creation of ad groups, setting and management of keywords, selection of content network, and analysis advanced tools of ppc campaign (public, dimensions, themes).

Submitted by Geyciane Santos (geyciane_thamires@hotmail.com) on 2015-06-22T14:20:17Z No. of bitstreams: 1 Tese - Klessius Renato Berlt.pdf: 972646 bytes, checksum: c127b522da4fc3719f61df80976a23ad (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-06-24T13:07:06Z (GMT) No. of bitstreams: 1 Tese - Klessius Renato Berlt.pdf: 972646 bytes, checksum: c127b522da4fc3719f61df80976a23ad (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-06-24T13:07:02Z (GMT) No. of bitstreams: 1 Tese - Klessius Renato Berlt.pdf: 972646 bytes, checksum: c127b522da4fc3719f61df80976a23ad (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-06-24T14:44:22Z (GMT) No. of bitstreams: 1 Tese - Klessius Renato Berlt.pdf: 972646 bytes, checksum: c127b522da4fc3719f61df80976a23ad (MD5) / Made available in DSpace on 2015-06-24T14:44:22Z (GMT). No. of bitstreams: 1 Tese - Klessius Renato Berlt.pdf: 972646 bytes, checksum: c127b522da4fc3719f61df80976a23ad (MD5) Previous issue date: 2012-12-19 / CNPQ - Conselho Nacional de Desenvolvimento Científico e Tecnológico / In this work we address the problem of selecting keywords for contextual advertising systems in two di erent scenarios: web pages and short texts. We deal with the problem of selecting keywords from web pages using machine learning. While traditional machine learning approaches usually have the goal of selecting keywords considered as good by humans. The new machine learning strategy proposed drives the selection by the expected impact of the keyword in the nal quality of the ad placement system, which we name here as ad collection aware keyword selection (also referred in this work as ACAKS). This new approach relies on the judgement of the users about the ads each keyword can retrieve. Although this strategy requires a higher e ort to build the training set than previous approaches, we believe the gain obtained in recall is worth enough to make the ad collection aware approach a better choice. In experiments we performed with an ad collection and considering features proposed in a previous work, we found that the new ad collection aware approach led to a gain of 62% in recall over the baseline without dropping the precision values. Besides the new alternative to select keywords, we also study the use of features extracted from the ad collection in the task of selecting keywords. We also present three new methods to extract keywords from web pages which require no learning process and use Wikipedia as an external source of information to support the keyword selection. The information used from Wikipedia includes the titles of articles, co-occurrence of keywords and categories associated with each Wikipedia de nition. Experimental results show that our methods are quite competitive solutions for the task of selecting good keywords to represent target web pages, albeit being simple, e ective and time e cient. Besides selecting keywords from web pages we also study methods for selecting keywords from short texts. Short texts have became a very popular way users adopt for publishing content on the web. Every day, millions of users post their thoughts, needs and feelings on the Web through systems, such as social networks like Facebook and Twitter, or spaces for comments on news web sites. Much of these systems' revenue is from contextual advertising systems, thus selecting keywords in this new scenario raise as a new challenge. We propose and study a novel family of methods which uses the connectivity information present on Wikipedia to discover the most related concepts on each short textual unit. We also used the proposed methods as a new set of features on a Machine Learning Framework to boost the quality of the results obtained. We show that this approach presents a good performance and outperforms the best baselines by more than 35%. Finally, we apply the ACAKS approach on short texts and it yielded good results, outperforming a traditional machine learning approach by more than 80% in precision and 80% in recall. / Neste trabalho, nós estudamos o problema de seleção de palavras-chave para sistemas de publicidade contextualizada em dois diferentes cenários: páginas web e textos curtos. Nós lidamos com o problema de seleção de palavras-chave em páginas web utilizando aprendizado de máquina. Abordagens tradicionais baseadas em aprendizado de máquina geralmente possuem como objetivo selecionar palavras-chave consideradas como relevantes por um conjunto de usuários. Entretanto, a nova estratégia proposta nesse trabalho objetiva selecionar palavras-chave que gerem o melhor resultado na qualidade final do sistema de seleção de publicidade. A esta estratégia, nós demos o nome de ad collection aware keyword selection (também chamada de ACAKS). Esta nova abordagem baseia-se no julgamento dos usuário em relação às propagandas com as quais cada palavra-chave _e relacionada pelo sistema de seleção de publicidade. Apesar desta estratégia demandar um alto esforço para rotular o conjunto de treino em relação _as abordagens tradicionais, nós acreditamos que o ganho obtido em revocação é suficiente para fazer com que o ACAKS seja uma melhor alternativa. Nos experimentos que nós realizamos com uma coleção de anúncios e considerando as características propostas em um trabalho anterior, nós descobrimos que a nova abordagem proposta levou a um ganho de 62% em revocação em relação ao baseline utilizado sem perder precisão. Além desta nova alternativa para selecionar palavras-chave, nós estudamos ainda a utilização do conjunto de características estraída da coleção de anúncios para selecionar palavras-chave. Nós também apresentamos três novos métodos para extrair palavras chave de páginas web que não necessitam de treino e usam a Wikipédia como fonte externa de informação. A informação usada da Wikipédia inclui os títulos dos artigos, co ocorrência de palavras chave e categorias associadas com cada artigo da Wikipédia. Resultados experimentais mostram que nossos métodos são soluções competitivas para selecionar boas palavras-chave que representem bem o conteúdo de páginas web, enquanto se mantém simples eficientes. Além da seleção de palavras-chave de paginas web nós também estudamos métodos para selecionar palavras-chave em textos curtos. Textos curtos tem se tornado uma maneira muito popular que os usuários encontraram para publicar conteúdo na web. Todos os dias, milhões de usuários postam seus pensamentos, necessidades e sentimentos na web através de sistemas de redes sociais, como Facebook e Twitter, ou espaços para comentários em sites de notícias. Grande parte da renda destes sistemas _e proveniente de publicidade contextualizada, desta forma selecionar palavras-chave neste novo cenário surge como um novo desafio. Nós propomos e estudamos uma nova família de métodos que utiliza a informação de conectividade presente na Wikipédia para descobrir os conceitos mais relacionados em cada texto curto. Utilizamos também os métodos propostos como um novo conjunto de características em um Framework de aprendizado de máquina para melhorar a qualidade dos resultados obtidos. Nós mostramos que esta abordagem apresenta um bom desempenho e supera o melhor baseline em cerca de 35%. Finalmente, nós aplicamos a abordagem ACAKS em textos curtos e ele gerou bons resultados, superando uma abordagem tradicional baseada em aprendizado de máquina em cerca de 80% tanto em termos de precisão quanto revocação.

Cognitive limitations such as those described in Miller's (1956) work on channel capacity and Cowen's (2001) on short-term memory are factors in determining user cognitive load and in turn task performance. Inappropriate user cognitive load can reduce user efficiency in goal realization. For instance, if the user's attentional capacity is not appropriately applied to the task, distractor processing can tend to appropriate capacity from it. Conversely, if a task drives users beyond their short-term memory envelope, information loss may be realized in its translation to long-term memory and subsequent retrieval for task base processing. To manage user cognitive capacity in the task of text search the interface should allow users to draw on their powerful and innate pattern recognition abilities. This harmonizes with Johnson-Laird's (1983) proposal that propositional representation is tied to mental models. Combined with the theory that knowledge is highly organized when stored in memory an appropriate approach for cognitive load optimization would be to graphically present single documents, or clusters thereof, with an appropriate number and type of descriptors. These descriptors are commonly words and/or phrases. Information theory research suggests that words have different levels of importance in document topic differentiation. Although key word identification is well researched, there is a lack of basic research into human preference regarding query formation and the heuristics users employ in search. This lack extends to features as elementary as the number of words preferred to describe and/or search for a document. Contrastive understanding these preferences will help balance processing overheads of tasks like clustering against user cognitive load to realize a more efficient document retrieval process. Common approaches such as search engine log analysis cannot provide this degree of understanding and do not allow clear identification of the intended set of target documents. This research endeavours to improve the manner in which text search returns are presented so that user performance under real world situations is enhanced. To this end we explore both how to appropriately present search information and results graphically to facilitate optimal cognitive and perceptual load/utilization, as well as how people use textual information in describing documents or constructing queries.

<p>Bakgrund: Traditionellt sett har två från varandra separata förhållanden dominerat marknaden, konkurrens och samarbete. Företag förväntas ofta delta i skilda relationer med sina konkurrenter respektive samarbetspartners. Det går emellertid att finna företag som både konkurrerar och samarbetar med samma företag, något som brukar benämnas som en co-opetitiv relation. En sådan relation går att återfinna inom den svenska försvarsindustrins offsetrelationer. </p><p>Syfte: Syftet med denna magisteruppsats är att beskriva och förklara hur samarbete och konkurrens förenas i en och samma relation, nämligen en offsetrelation, samt utreda vilka aspekter som är av vikt för att det co- opetitiva förhållandet i nämnda relation skall vara fördelaktigt för alla inblandade parter. </p><p>Genomförande: Denna studie grundar sig främst på fyra intervjuer med representanter från organisationer inom försvarsindustrin. Vi har även till viss del använt oss av vår kandidatuppsats och data som samlades in till denna. </p><p>Resultat: Vi har funnit att den co-opetitiva relation som återfinns i försvarsindustrin har en högre grad av samarbete än konkurrens. För att hantera situationen där både konkurrens och samarbete förekommer utnyttjas en mellanhand i form av en industriförening. Den enskilt viktigaste aspekten är skapandet av förtroende mellan parterna. Det är även viktigt att företagen har realistiska förväntningar med relationen och är medvetna om dess för- och nackdelar.</p>

<p><strong>Sammanfattning</strong></p><p><strong> </strong></p><p>Det är inte bara elever med dyslexi som har läs- och skrivsvårigheter, utan problemet har ökat överallt i vårt moderna samhälle. Kraven på att läsa och ha god läsförståelse ökar i takt med att allt mer information skickas till oss via media, internet och post. Detta problem medförde att vi på den skola jag arbetar startade ett läsprojekt för att öka elevernas läsförståelse och därmed också deras resultat i skolan. Syftet med mitt arbete är att ta reda på vilka svårigheter och orsaker det finns för elever som har läs- och skrivsvårigheter, samt hur man ökar deras läsförståelseförmåga. Kan elever bara genom att läsa mera, kunna förbättra sina prestationer i läsförståelse. För att få ett svar på detta har jag undersökt elevers resultat av läsförståelsediagnoser. Resultaten presenteras utifrån en stanineskala som är en standardskala där elevernas poäng överförs till en niogradig skala. Ett staninevärde på fem motsvarar medelvärde. Sammanlagt nittiosju elever i samma ålder har kartlagts under högstadietiden. Resultatet vid undersökningen blev att läsförståelsen förbättrades för de svaga läsarna. Det visade sig också att de som var bra i sin läsförståelse i årskurs sju, sänkte sina resultat och närmade sig medelstanine fem. Ökad lästid i skolan har gjort att eleverna ökat sin läsförståelse. Däremot krävs det en utveckling av projektet, där samtalet kring det man läser sätts i fokus. Samtal ökar elevers förståelse och reflekterande.</p> / <p><strong>Abstract</strong></p><p>The problem with dyslexia has increased everywhere in our modern society. Requirements of proficiency in reading and comprehension skills, increases at a similar speed to that which information is disseminated. This problem led to a reading project in the school where I work. The aim was to increase pupils reading, comprehension and also their overall performance. Is it a possibility that by just reading more in school, pupils can improve their performance? To find and answer I have researched the pupils results from a reading comprehension diagnosis. The results are presented from a stanine scale, a standard scale where pupils points transfers to a nine degree scale. A stanine value of five is equal to mean and the lowest values are one and two. The reading diagnosis was undertaken by 97 pupils in the same age. The fist was carried out in autumn term of year seven and then every autumn up to year nine. The results show that reading comprehension improved for weaker readers from level one and two in year seven, to level three and four in year nine. The results also showed that pupils with good abilities in year seven lowered their results to middle stanine five in year nine. More time for reading in school shows that pupils increase their reading comprehension. However, the project needs to develop further, with focus on discussions following the reading of a text.</p>

Bakgrund: Traditionellt sett har två från varandra separata förhållanden dominerat marknaden, konkurrens och samarbete. Företag förväntas ofta delta i skilda relationer med sina konkurrenter respektive samarbetspartners. Det går emellertid att finna företag som både konkurrerar och samarbetar med samma företag, något som brukar benämnas som en co-opetitiv relation. En sådan relation går att återfinna inom den svenska försvarsindustrins offsetrelationer. Syfte: Syftet med denna magisteruppsats är att beskriva och förklara hur samarbete och konkurrens förenas i en och samma relation, nämligen en offsetrelation, samt utreda vilka aspekter som är av vikt för att det co- opetitiva förhållandet i nämnda relation skall vara fördelaktigt för alla inblandade parter. Genomförande: Denna studie grundar sig främst på fyra intervjuer med representanter från organisationer inom försvarsindustrin. Vi har även till viss del använt oss av vår kandidatuppsats och data som samlades in till denna. Resultat: Vi har funnit att den co-opetitiva relation som återfinns i försvarsindustrin har en högre grad av samarbete än konkurrens. För att hantera situationen där både konkurrens och samarbete förekommer utnyttjas en mellanhand i form av en industriförening. Den enskilt viktigaste aspekten är skapandet av förtroende mellan parterna. Det är även viktigt att företagen har realistiska förväntningar med relationen och är medvetna om dess för- och nackdelar.

Nowadays, digital imaging is mostly based on the paradigm that a combinations of a small number of so-called primary colors is sufficient to represent any visible color. For instance, most cameras usepixels with three dimensions: Red, Green and Blue (RGB). Such low dimensional technology suffers from several limitations such as a sensitivity to metamerism and a bounded range of wavelengths. Spectral imaging technologies offer the possibility to overcome these downsides by dealing more finely withe the electromagnetic spectrum. Mutli-, hyper- or ultra-spectral images contain a large number of channels, depicting specific ranges of wavelength, thus allowing to better recover either the radiance of reflectance of the scene. Nevertheless,these large amounts of data require dedicated methods to be properly handled in a variety of applications. This work contributes to defining what is the useful information that must be retained for visualization on a low-dimensional display device. In this context, subjective notions such as appeal and naturalness are to be taken intoaccount, together with objective measures of informative content and dependency. Especially, a novel band selection strategy based on measures derived from Shannon's entropy is presented and the concept of spectral saliency is introduced.

This thesis addresses the problems of phonemic variability and confusability from the pronunciation modeling perspective for an automatic speech recognition (ASR) system. In particular, several research directions are investigated. First, automatic grapheme-to- phoneme (g2p) and phoneme-to-phoneme (p2p) converters are developed that generate alternative pronunciations for in-vocabulary as well as out-of-vocabulary (OOV) terms. Since the addition of alternative pronunciation may introduce homophones (or close homophones), there is an increase of the confusability of the system. A novel measure of this confusability is proposed to analyze it and study its relation with the ASR performance. This pronunciation confusability is higher if pronunciation probabilities are not provided and can potentially severely degrade the ASR performance. It should, thus, be taken into account during pronunciation generation. Discriminative training approaches are, then, investigated to train the weights of a phoneme confusion model that allows alternative ways of pronouncing a term counterbalancing the phonemic confusability problem. The objective function to optimize is chosen to correspond to the performance measure of the particular task. In this thesis, two tasks are investigated, the ASR task and the KeywordSpotting (KWS) task. For ASR, an objective that minimizes the phoneme error rate is adopted. For experiments conducted on KWS, the Figure of Merit (FOM), a KWS performance measure, is directly maximized.