Devant des collections massives et hétérogènes de données, les systèmes de RI doivent désormais pouvoir appréhender des comportements d'utilisateurs aussi variés qu'imprévisibles. L'objectif de notre travail est d'évaluer la façon dont un même utilisateur verbalise un besoin informationnel à travers un énoncé de type « expression libre » (appelé langage naturel) et un énoncé de type mots-clés (appelé langage de requêtes). Pour cela, nous nous situons dans un contexte applicatif, à savoir des demandes de remboursement des utilisateurs d'un moteur de recherche dédié à des études économiques en français. Nous avons recueilli via ce moteur, les deux types d'énoncés sur 5 années consécutives totalisant un corpus de 1398 demandes en langage naturel et de 3427 requêtes. Nous avons alors comparé l'expression en tant que tel du besoin informationnel et mis en avant ce qu'apportait, en termes d'informations et de précisions, le recours à l'un ou l'autre du langage utilisé. / With the massive and heterogeneous web document collections, IR system must analyze the behaviors of users which are unpredictable and varied. The approach described in this thesis provides a comparison of the verbalizations for both natural language and web query for the same information need by the same user. For this, we used data collected (i.e. users' complaints in natural language and web queries) through a search engine dedicated to economic reports in French over 5 consecutive years totaling a corpus of 1398 natural language requests and 3427 web queries. Then, we compared the expression of the information need and highlighted the contributions in terms of information and clarification, the use of either language used.

Submitted by JÚLIO HEBER SILVA (julioheber@yahoo.com.br) on 2017-10-19T16:57:21Z No. of bitstreams: 2 Dissertação - João Batista Pereira Matos Júnior - 2017.pdf: 8366739 bytes, checksum: 13cc5b776da9444f310561caaa0e86d4 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2017-10-20T10:12:26Z (GMT) No. of bitstreams: 2 Dissertação - João Batista Pereira Matos Júnior - 2017.pdf: 8366739 bytes, checksum: 13cc5b776da9444f310561caaa0e86d4 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-10-20T10:12:26Z (GMT). No. of bitstreams: 2 Dissertação - João Batista Pereira Matos Júnior - 2017.pdf: 8366739 bytes, checksum: 13cc5b776da9444f310561caaa0e86d4 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-09-15 / Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq / Users influence analysis over other users has been highlighted in studies involving online social networks, especially for the social network known as Twitter. However, there is still room for studies which analyze the influence that a user a exerts on another user e, based on the frequency of interactions from e dedicated to a in the social network. In the case of Twitter, three interactions are commonly used by users: the like, the mention and the retweet. This work assumes that a direct way of measuring the influence of a user a over another user e on Twitter is to observe the number of interactions of e with a over time. In this sense, a new concept called loyalty is proposed to define a specific and personalized type of influence, in which users, through their interactions, demonstrate preference by some peers in the social network (i.e., through the frequency of the interactions). Three aspects of loyalty were analyzed: i) intensity of interaction with the preferred user; ii) probability of interaction with users with whom there is loyalty, and iii) predictability of user interactions with their peers. Experiments done on a large sample of Twitter users reveal that the vast majority of users have loyalty to some user. In addition, the type of interaction and cultural aspects such as the written language used in the tweets differently affect the three aspects of fidelity considered. The paper also offers suggestions on how information derived from loyalty may be useful for future work related to influence on Twitter. / Análise da Fidelidade no Comportamento dos Usuários do Twitter– Um Estudo a Respeito da Influência Social com uma Visão Local Para Redes Sociais Online. A análise da influência de usuários sobre outros tem tido destaque em estudos envolvendo as redes sociais online, em especial a rede social Twitter. Entretanto, ainda há carência de trabalhos que analisem a influência que um usuário a tem sobre outro usuário e, com base na quantidade de interações que e tem com a na rede social. No caso do Twitter, três interações são comumente utilizadas pelos usuários: o curtir (ou gostar), o retweet e a menção. Este trabalho parte do princípio que uma forma direta de avaliar a influência que um usuário a tem sobre um usuário e no Twitter é observar o número de interações de e com a ao longo do tempo. Nesse sentido, propõe-se um novo conceito, denominado fidelidade, para definir um tipo específico e personalizado de influência, em que os usuários, por meio de suas interações, demonstram preferência (através da frequência de interações) por alguns de seus pares na rede social. Analisou-se três aspectos da fidelidade: i) intensidade de interação com o usuário preferido; ii) probabilidade de interação com usuários aos quais há fidelidade e iii) previsibilidade do usuário ao interagir com seus pares. Experimentos feitos em uma grande amostra de usuários, revelam que a grande maioria dos usuários têm fidelidade com algum outro usuário. Além disso, o tipo de interação e aspectos culturais como a língua escrita utilizada afetam de modo diverso os três aspectos de fidelidade considerados. O trabalho também apresenta sugestões de como as informações derivadas sobre a fidelidade podem ser úteis para trabalhos futuros relacionados à influência no Twitter.

La prise en compte des enjeux environnementaux est un sujet très présent dans notre société actuelle. Dans le domaine du développement de produits, l'Eco-conception est une démarche qui permet la considération de ces enjeux en proposant de réduire les impacts environnementaux des produits tout au long de leur cycle de vie. La phase d'utilisation du cycle de vie est une étape cruciale puisque le mode d'utilisation des produits peut avoir des conséquences non négligeables sur leur performance environnementale. Nous proposons dans cette thèse d'enrichir la compréhension de cette phase d'utilisation en mettant en évidence les composantes Kansei qui jouent un rôle dans l'interaction de l'utilisateur avec le produit et qui peuvent être intégrées en amont de la conception de produits à faible impact environnemental. Notre démarche permet de mieux renseigner la phase d'utilisation, contribuant ainsi à la maitrise de la performance environnementale des produits. Nous démontrons à travers notre recherche que l'utilisateur peut être défini, non seulement par des informations basiques que nous retrouvons communément dans la Conception Centrée Utilisateur, mais également à partir d'informations subjectives apportées par la dimension Kansei. A travers nos expérimentations, nous mettons en application deux attributs EcoKansei correspondants aux valeurs et aux émotions afin d'illustrer la modélisation utilisateur pour la conception de produits à faible impact environnemental. L'approche que nous proposons vient en complément au projet EcoUse qui vise à développer une méthodologie d'Eco-conception centrée utilisateur. Les apports de notre démarche sont multiples. Du point de vue de la recherche, une mise en relation de l'Eco-conception et du Kansei, qui sont à la base complètement déconnectées entraine un enrichissement mutuel entre ces deux approches. Du point de vue industriel, une démarche d'Eco-conception appuyée par les études Kansei doit permettre la conception de nouveaux produits qui auront l'avantage d'être à la fois mieux acceptés par les utilisateurs car en adéquation avec leur sensibilité environnementale et en même temps moins impactants pour l'environnement. / The consideration of environmental issues is a very strong topic in our society nowadays. In the field of Product Development, Ecodesign is a methodology that allows the consideration of these issues by proposing to reduce the environmental impacts of products throughout their life cycle. The use phase of the life cycle is a critical step as the way how the products are managed can have significant impact on their environmental performance. We propose in this thesis to enrich the understanding of the use phase by highlighting the Kansei Information that can play a major role in the interaction between the user and the product and thus can be integrated in the early phase of the Ecodesign process. Our approach provides a better understanding the use phase, by contributing to the mastery of the environmental performance of products. Our research points out that the user can be defined not only from basic information commonly used in the User Centered Design, but also from subjective information brought by the Kansei dimension. We carry out experiments in which we implement two EcoKansei attributes corresponding to the values and emotions in order to illustrate user modeling for Ecodesign. The approach we propose is a part of EcoUse project that aims to develop a methodology for user-centered Ecodesign. Various contributions of our approach can be pointed out. For the Research, linking Ecodesign with the Kansei studies, which are basically unconnected leads to mutual enrichment between these two approaches. For Industry, an Eco-design approach supported by Kansei Information enables the design of new products which will have the benefits of both providing less impacts to the environment, and at the same time being more accepted by users as these products match with their environmental sensitivity.

Online social networks (OSNs) are Web platforms providing different services to facilitate social interaction among their users. A particular kind of OSNs is the location-based social network (LBSN), which adds services based on location. One of the most important challenges in LBSNs is the link prediction problem. Link prediction problem aims to estimate the likelihood of the existence of future friendships among user pairs. Most of the existing studies in link prediction focus on the use of a single information source to perform predictions, i.e. only social information (e.g. social neighborhood) or only location information (e.g. common visited places). However, some researches have shown that the combination of different information sources can lead to more accurate predictions. In this sense, in this thesis we propose different link prediction methods based on the use of different information sources naturally existing in these networks. Thus, we propose seven new link prediction methods using the information related to user membership in social overlapping groups: common neighbors within and outside of common groups (WOCG), common neighbors of groups (CNG), common neighbors with total and partial overlapping of groups (TPOG), group naïve Bayes (GNB), group naïve Bayes of common neighbors (GNB-CN), group naïve Bayes of Adamic-Adar (GNB-AA) and group naïve Bayes of Resource Allocation (GNB-RA). Due to that social groups exist naturally in networks, our proposals can be used in any type of OSN.We also propose new eight link prediction methods combining location and social information: Check-in Observation (ChO), Check-in Allocation (ChA), Within and Outside of Common Places (WOCP), Common Neighbors of Places (CNP), Total and Partial Overlapping of Places (TPOP), Friend Allocation Within Common Places (FAW), Common Neighbors of Nearby Places (CNNP) and Nearby Distance Allocation (NDA). These eight methods are exclusively for work in LBSNs. Obtained results indicate that our proposals are as competitive as state-of-the-art methods, or better than they in certain scenarios. Moreover, since our proposals tend to be computationally more efficient, they are more suitable for real-world applications. / Redes sociais online (OSNs) são plataformas Web que oferecem serviços para promoção da interação social entre usuários. OSNs que adicionam serviços relacionados à geolocalização são chamadas redes sociais baseadas em localização (LBSNs). Um dos maiores desafios na análise de LBSNs é a predição de links. A predição de links refere-se ao problema de estimar a probabilidade de conexão futura entre pares de usuários que não se conhecem. Grande parte das pesquisas que focam nesse problema exploram o uso, de maneira isolada, de informações sociais (e.g. amigos em comum) ou de localização (e.g. locais comuns visitados). Porém, algumas pesquisas mostraram que a combinação de diferentes fontes de informação pode influenciar o incremento da acurácia da predição. Motivado por essa lacuna, neste trabalho foram desenvolvidos diferentes métodos para predição de links combinando diferentes fontes de informação. Assim, propomos sete métodos que usam a informação relacionada à participação simultânea de usuários en múltiples grupos sociais: common neighbors within and outside of common groups (WOCG), common neighbors of groups (CNG), common neighbors with total and partial overlapping of groups (TPOG), group naïve Bayes (GNB), group naïve Bayes of common neighbors (GNB-CN), group naïve Bayes of Adamic-Adar (GNB-AA), e group naïve Bayes of Resource Allocation (GNB-RA). Devido ao fato que a presença de grupos sociais não está restrita a alguns tipo de redes, essas propostas podem ser usadas nas diversas OSNs existentes, incluindo LBSNs. Também, propomos oito métodos que combinam o uso de informações sociais e de localização: Check-in Observation (ChO), Check-in Allocation (ChA), Within and Outside of Common Places (WOCP), Common Neighbors of Places (CNP), Total and Partial Overlapping of Places (TPOP), Friend Allocation Within Common Places (FAW), Common Neighbors of Nearby Places (CNNP), e Nearby Distance Allocation (NDA). Tais propostas são para uso exclusivo em LBSNs. Os resultados obtidos indicam que nossas propostas são tão competitivas quanto métodos do estado da arte, podendo até superá-los em determinados cenários. Ainda mais, devido a que na maioria dos casos nossas propostas são computacionalmente mais eficientes, seu uso resulta mais adequado em aplicações do mundo real.

Organisationer står idag inför flera olika hot mot deras IT-säkerhet där ett av de vanligaste hoten är skadliga användarbeteenden som främst orsakas av interna användare. Det kan vara svårt att veta för organisationer vad för användarbeteenden som kan utgöra ett hot samt vilka orsaker som kan bidrar till dessa beteenden. Det är i dagens samhälle viktigt för organisationer att förbereda sig samt vara medvetna om de hot en användare utgör för att kunna vidta de rätta åtgärderna om det skulle uppstå. Syftet med denna studie är att undersöka vilka orsaker till användarnas beteenden som utgör ett hot för en organisations IT-säkerhet och vilka åtgärder som har vidtagits. En kvalitativ metod i form av fem olika intervjuer har valts där en intervjuguide låg som grund till intervjufrågorna. En individuell intervju hölls med en användare av Högskolan i Borås samt en gruppintervju med IT-avdelningen från Högskolan i Borås. Studien resulterade i att 10 användarbeteenden, 25 orsaker och 22 vidtagna åtgärder framkom samt att det finns relationer mellan dem. Det kan vara svårt för organisationer att vara helt förberedda på hot men det är enligt vår studie möjligt att identifiera användarbeteenden, orsaker samt åtgärder. Med utbildning kan organisationer göra sina användare mer säkerhetsmedvetna och därmed minska riskerna för de skador användarbeteenden kan utgöra. / Organizations today are facing several different threats to their IT security where one of the most common threats is malicious user behaviors that are mainly caused by internal users. It can be difficult for organizations to know what user behaviors can pose a threat and what causes can contribute to these behaviors. In today's society, it is important for organizations to prepare and be aware of the threats a user poses in order to be able to take the right measures if they should arise. The language of this study is written in swedish and the purpose of this study is to investigate what causes in users' behavior constitute a threat to an organization's IT security and what measures have been taken. A qualitative method in the form of five different interviews has been chosen where an interview guide was the basis for the interview questions. An individual interview was held with a user of the University of Borås and a group interview with the IT department from the University of Borås. The study resulted in 10 user behaviors, 25 causes and 22 measures taken and that there are connections and relationships between them. It can be difficult for organizations to be fully prepared for threats, but according to our study it is possible to identify user behaviors, causes and measures. With education, organizations can make their users more security-conscious and thus reduce the risks of the damage that user behavior can cause.

The users´ behaviors play an important role in securing information systems. At the same time, the users´ bad behaviors end-up in making them victims to e-crime attacks. To emphasize the positive side of users´ behaviors, the reasons for the bad behaviors must be investigated. In this research, e-crimes on users in Sweden were studied using the protection motivation theory and the theory of planned behavior in order to understand what variables govern the user behaviors. The information retrieved from the literature review and the web survey were used to answer the research question about which variables within the two used theories affect the user behaviors in connection to e-crimes. It turned out that perceived vulnerability, perceived severity, and user-efficacy have significant effect on the selected user behavior. Besides, the analysis of the results showed that IT/IS-knowledge is a determinant factor that affects all the variables of the protection motivation theory.

The rapid growth of Internet Traffic has emerged as a major issue due to the rapid development of various network applications and Internet services. One of the challenges facing Internet Service Providers (ISPs) is to optimize the performance of their networks in the face of continuously increasing amounts of IP traffic while guaranteeing some specific Quality of Services (QoS). Therefore it is necessary for ISPs to study the traffic patterns and user behaviors in different localities, to estimate the application usage trends, and thereby to come up with solutions that can effectively, efficiently, and economically support their users’ traffic. The main objective of this thesis is to analyze and characterize traffic in a local multi-service residential IP network in Sweden (referred to in this report as “Network North”). The data about the amount of traffic was measured using a real-time traffic-monitoring tool from PacketLogic. Traffic from the monitored network to various destinations was captured and classified into 5 ring-wise locality levels in accordance with the traffic’s geographic destinations: traffic within Network North and traffic to the remainder of the North of Sweden, Sweden, Europe, and World. Parameters such as traffic patterns (e.g., traffic volume distribution, application usage, and application popularity) and user behavior (e.g., usage habits, user interests, etc.) at different geographic localities were studied in this project. As a result of a systematic and in-depth measurement and the fact that the number of content servers at the World, Europe, and Sweden levels are quite large, we recommend that an intelligent content distribution system be positioned at Level 1 localities in order to reduce the amount of duplicate traffic in the network and thereby removing this traffic load from the core network. The results of these measurements provide a temporal reference for ISPs of their present traffic and should allow them to better manage their network. However, due to certain circumstances the analysis was limited due to the set of available daily traffic traces. To provide a more trustworthy solution, a relatively longer-term, periodic, and seasonal traffic analysis could be done in the future based on the established measurement framework. / Den ökande tillväxten av Internet Trafik har blivit en viktig fråga med anledning av den snabba utvecklingen av olika internetbaserade applikationer och tjänster. En av utmaningarna för Internet leverantörerna är att optimera prestandan i sina nät inför de ständigt ökande datamängderna och samtidigt garantera kvalitet på tjänsterna (QoS). Därför är det nödvändigt för Internetleverantörer att studera trafikmönster och lokala differentierade användarbeteenden, för att uppskatta trender av nyttjande av internettjänster, och därmed komma med lösningar som effektivt och ekonomiskt stödja deras kunders trafik. Det främsta syftet med denna avhandling är att analysera och karaktärisera internettrafiken i ett lokalt IP baserat multiservicenätverk i Sverige (i denna rapport avseende "Network North"). Uppgifterna om trafikmängden mättes i realtid med ett övervakningsverktyg från PacketLogic. Trafik till och från det övervakade nätverkets olika destinationer fångades upp och delades in i 5 cirkelliknande lokaliseringsnivåer i enlighet med geografiska trafikdestinationer: trafik inom nätverket North och till resten av norra Sverige, Sverige, Europa och världen. Parametrar som trafikmönster (t.ex. distribuerad internettrafik mängd, användning av olika tjänster och applikationer med dess popularitet) och användarbeteenden (t.ex. användar-vanor och intressen, etc.) på olika geografiska lokaliseringsnivåer har studerades i inom projekt. Som ett resultat av de systematiska och djupgående internetmätningar med det faktum av det stora antalet existerande tjänsteinnehållsservrar som ofta finns placerad långt ifrån slutanvändaren, ute i världen eller i Europa som är ganska så många till antalet. Rekommenderar vi att ett intelligent tjänstedistributionssystem appliceras närmre slutanvändaren på en regional nivå, för att minska på dagens onödiga omfattande duplicerande internettrafik i nom stamnäteten. Resultaten av dessa trafikmätningar av internettrafik ger en tidsmässig referens för Internetleverantörerna av deras nuvarande trafik och bör göra det möjligt för dem att bättre hantera sin nätverksinfrastruktur. Men på grund av vissa omständigheter begränsades mätanalysen på grund av möjliga och tillgängliga tidrammar att utföra dagliga trafikmätningsuppsättningen. För att ge en mer tillförlitlig lösning kan en på en längre sikt, periodisk och säsongsbunden trafikanalys göras i framtiden, baserat på den etablerade mätinfrastrukturen.

This diploma thesis deals with the topic of video on demand platforms and is more closely focused on one of the main worldwide available platform managed by Netflix. The thesis describes the history of the service and the basic principles and theories on the basis of which this service works. Attention is devoted to the functioning of this platform in the Czech Republic and the development of the user interface and expansion of the catalogue in order to gain more attention from the Czech audience. The research part of the thesis provides insights into the way how the platform is used by Czech users, specifically among 20-27 years old students. The qualitative survey examined the period and ways of how Netflix became known among the users, how users gained access to video content before subscribing Netflix and how the platform influenced their series and movie consumption habits. The research also focused on the perception of the offered content, on the form and price of the subscription and on the user-friendliness and functionality of the platform. The other aim of the research was to find out how much time users spend watching movies and series and in which situations they are looking for this activity. Part of the research also looked at changes in the use of the streaming service during the...

The social media app TikTok, owned by the Chinese Company ByteDance, has become a worldwide success with over one billion monthly active users due to an algorithm that enables users to consume individually tailored content. However, it was also part of pol itical confrontations between countries like the USA and China due to allegedly security risks. Moreover, the app could be classified as a persuasive technology with potential on Students in Sweden with quantitati ethical and privacy concerns . A case study ve and qualitative research methods was conducted to understand user behavior and the app's impact on users. The former was a survey with 36 participants, and the latter interviews with 6 participants. The case study results indicate, among other things, t hat the participants consume content beyond entertainment, evaluate the algorithm as accurate, do not unambiguously experience a filter bubble, and asses the app as addictive. Despite ethical and privacy concerns, the app has potential for different use ca ses, such as marketing or education. / Den social media appen TikTok, som ägs av det kinesiska företaget ByteDance, har blivit en världssuccé med över en miljard aktiva användare varje månad tack vare en algoritm som gör det möjligt för användarna att konsumera individuellt anpassat innehåll. D en har dock också varit en del av politiska konfrontationer mellan länder som USA och Kina på grund av påstådda säkerhetsrisker. Appen kan klassificeras som en övertalningsteknik med dess potentiella etiska och integritetsrelaterade problem. För att förstå användarnas beteende och appens inverkan på användarna genomfördes en fallstudie om studenter i Sverige med både kvantitativa och kvalitativa forskningsmetoder. Den förstnämnda var en enkät med 36 deltagare och den sistnämnda intervjuer med 6 deltagare. F allstudiens resultat visar bland annat att deltagarna konsumerar innehåll utöver underhållning, bedömer algoritmen som korrekt, upplever inte entydigt ett filter bubble och bedömer appen som beroendeframkallande. Appen har trots etiska och integritetsrelaterade problem, potential för olika användningsområden, t.ex. marknadsföring eller utbildning.

Diese Dissertation untersucht Geräte, die Praktiker verwenden, um die Wiederverwendung von digitalen Bibliotheksmaterialien zu entdecken. Der Autor führt zwei Verifikationsstudien durch, in denen zwei zuvor angewandte Strategien untersucht werden, die Praktiker verwenden, um die Wiederverwendung digitaler Objekte zu identifizieren, insbesondere Google Images Reverse Image Lookup (RIL) und eingebettete Metadaten. Es beschreibt diese Strategiebeschränkungen und bietet einen neuen, einzigartigen Ansatz zur Verfolgung der Wiederverwendung, indem der Suchansatz des Autors basierend auf dem Benennungsverhalten von Benutzerdateien verwendet wird. Bei der Untersuchung des Nutzens und der Einschränkungen von Google Images und eingebetteten Metadaten beobachtet und dokumentiert der Autor ein Muster des Benennungsverhaltens von Benutzerdateien, das vielversprechend ist, die Wiederverwendung durch den Praktiker zu verbessern. Der Autor führt eine Untersuchung zur Bewertung der Dateibenennung durch, um dieses Muster des Verhaltens der Benutzerdateibenennung und die Auswirkungen der Dateibenennung auf die Suchmaschinenoptimierung zu untersuchen. Der Autor leitet mehrere signifikante Ergebnisse ab, während er diese Studie fertigstellt. Der Autor stellt fest, dass Google Bilder aufgrund der Änderung des Algorithmus kein brauchbares Werkzeug mehr ist, um die Wiederverwendung durch die breite Öffentlichkeit oder andere Benutzer zu entdecken, mit Ausnahme von Benutzern aus der Industrie. Eingebettete Metadaten sind aufgrund der nicht persistenten Natur eingebetteter Metadaten kein zuverlässiges Bewertungsinstrument. Der Autor stellt fest, dass viele Benutzer ihre eigenen Dateinamen generieren, die beim Speichern und Teilen von digitalen Bildern fast ausschließlich für Menschen lesbar sind. Der Autor argumentiert, dass, wenn Praktiker Suchbegriffe nach den "aggregierten Dateinamen" modellieren, sie ihre Entdeckung wiederverwendeter digitaler Objekte erhöhen. / This dissertation explores devices practitioners utilize to discover the reuse of digital library materials. The author performs two verification studies investigating two previously employed strategies that practitioners use to identify digital object reuse, specifically Google Images reverse image lookup (RIL) and embedded metadata. It describes these strategy limitations and offers a new, unique approach for tracking reuse by employing the author's search approach based on user file naming behavior. While exploring the utility and limitations of Google Images and embedded metadata, the author observes and documents a pattern of user file naming behavior that exhibits promise for improving practitioner's discoverability of reuse. The author conducts a file naming assessment investigation to examine this pattern of user file naming behavior and the impact of file naming on search engine optimization. The author derives several significant findings while completing this study. The author establishes that Google Images is no longer a viable tool to discover reuse by the general public or other users except for industry users because of its algorithm change. Embedded metadata is not a reliable assessment tool because of the non-persistent nature of embedded metadata. The author finds that many users generate their own file names, almost exclusively human-readable when saving and sharing digital images. The author argues that when practitioners model search terms after the "aggregated file names" they increase their discovery of reused digital objects.