소셜 카탈로깅 서비스에서의 감정 기반 아이템 추천 기법

학위논문 (박사)-- 서울대학교 대학원 공과대학 전기·컴퓨터공학부, 2017. 8. 김형주.Social cataloging services allow users to catalog items, express subjective opinions, and communicate with other users. Users in social cataloging services can refer to others activities and opinions and obtain complementary information about items through the relationships with others. However, unlike a general social networking service where user behaviors are based on the connections between users, users in social cataloging services can participate and contribute to services and can obtain the information about items without links. In contrast to a general social networking service in which actions are performed based on connections between users, You can participate and contribute. In this doctoral dissertation, we classify users into two groups as connected users and isolated users and analyze usersbehaviors. Considering the characteristics of users who mainly focus on contents rather than relationships, we propose a tag emotion-based item recommendation scheme. Tags are the additional information about the item, and at the same time, it is a subjective estimation of users for items, which contains the users feelings and opinions on the item. Therefore, if we consider the emotions contained in tags, it is possible to obtain the recommendation result reflecting the users preferences or interest. In order to reflect the emotions of each tag, the ternary relationships between users, items, and tags are modeled by the three-order tensor, and new items are recommended based on the latent semantic information derived by a high order singular value decomposition technique. However, the data sparsity problem occurs because the number of items in which a user is tagged is smaller than the amount of all items. In addition, since the recommendation is based on the latent semantic information among users, items, and tags, the previous tagging histories of users and items are not considered. Therefore, in this dissertation, we use item-based collaborative filtering technique to generate additional data to build an extended data set. We also propose an improved recommendation method considering the user and item profiles. The proposed method is evaluated based on the actual data of social cataloging service. As a result, we show that the proposed method improves the recommendation performances compared to the collaborative filtering and other tensor-based recommendation methods.Chapter 1 Introduction 1 1.1 Research Motivation 1 1.2 Research Contributions 3 1.3 Dissertation Outline 5 Chapter 2 Backgrounds and Related Work 7 2.1 Online Social Networks and Social Cataloging Services 7 2.2 Terminologies 9 2.3 Related Work 12 2.3.1 Social Network Analysis 12 2.3.2 Item Recommendation 16 2.3.3 Emotion Analysis and Recommendation using emotions 20 Chapter 3 User Behavior in Social Cataloging Services 24 3.1 Motivation 24 3.2 Datasets 27 3.2.1 LibraryThing 27 3.2.2 Userstory Book 28 3.2.3 Flixster 30 3.2.4 Preliminary Analysis 31 3.3 Characteristics of Users in Social Cataloging Services 36 3.3.1 Assortativity 36 3.3.2 Reciprocity 37 3.3.3 Homophily 39 3.4 Isolated Users in Social Cataloging Service 41 3.5 Summary 48 Chapter 4 Tag Emotion Based Item Recommendation 51 4.1 Motivation 52 4.2 Weighting of Tags 55 4.2.1 Rating Based Tag Weight 55 4.2.2 Emotion Based Tag Weight 57 4.2.3 Overall Tag Weight 58 4.3 Tensor Factorization 59 4.3.1 High Order Singular Value Decomposition 60 4.4 A Running Example 62 4.5 Experimental Evaluation 66 4.5.1 Dataset 66 4.5.2 Experimental Results 68 4.6 Summary 76 Chapter 5 Improving Item Recommendation using Probabilistic Ranking 78 5.1 Motivation 78 5.2 Generating the additional data 79 5.3 BM25 based candidate ranking 81 5.4 Experimental Evaluation 84 5.4.1 Data addition 84 5.4.2 Recommendation Performances 87 5.5 Case Study 96 5.6 Summary 99 Chapter 6 Conclusions 100 Bibliography 103 초록 117Docto

Illusions of a ‘Bond’: Tagging Cultural Products across Online Platforms

Structured Abstract Purpose Most studies pertaining to social tagging focus on one platform or platform type, thus limiting the scope of their findings. This study explores social tagging practices across four platforms in relation to cultural products associated with the book Casino Royale, by Ian Fleming. Design/methodology/approach A layered and nested case study approach was used to analyze data from four online platforms: Goodreads, Last.fm, WordPress, and public library social discovery platforms. The top-level case study focuses on the book Casino Royale, by Ian Fleming, and its derivative products. The analysis of tagging practices in each of the four online platforms is nested within the top-level case study. ‘Casino Royale’ was conceptualized as a cultural product (the book), its derived products (e.g., movies, theme songs), as well as a keyword in blogs. A qualitative, inductive, and context-specific approach was chosen to identify commonalities in tagging practices across platforms whilst taking into account the uniqueness of each platform. Findings The four platforms comprise different communities of users, each platform with its own cultural norms and tagging practices. Traditional access points in the library catalogues focused on the subject, location, and fictitious characters of the book. User-generated content across the four platforms emphasized historical events and periods related to the book, and highlighted more subjective access points, such as recommendations, tone, mood, reaction, and reading experience. Revealing shifts occur in the tags between the original book and its cultural derivatives: Goodreads and library catalogues focus almost exclusively on the book, while Last.fm and WordPress make additional cross-references to a wider range of different cultural products, including books, movies, and music. The analyses also yield apparent similarities in certain platforms, such as recurring terms, phrasing and composite or multifaceted tags, as well as a strong presence of genre-related terms for the book and music. Originality/value The layered and nested case study approach presents a more comprehensive theoretical viewpoint and methodological framework by which to explore the study of user-generated metadata pertaining to a range of related cultural products across a variety of online platforms

User-Centered Categorization of Mood in Fiction

Readers articulate mood in deeply subjective ways, yet the underlying structure of users’ understanding of the media they consume has important implications for retrieval and access. User articulations might at first seem too idiosyncratic, but organizing them meaningfully has considerable potential to provide a better searching experience for all involved. The current study develops mood categories inductively for fiction organization and retrieval in information systems.We developed and distributed an open-ended survey to 76 fiction readers to understand their preferences with regard to the affective elements in fiction. From the fiction reader responses, the research team identified 161 mood terms and used them for further categorization.Our inductive approach resulted in 30 categories, including angry, cozy, dark, and nostalgic. Results include three overlapping mood families: Emotion, Tone/Narrative, and Atmosphere/Setting, which in turn relate to structures that connect reader-generated data with conceptual frameworks in previous studies.The inherent complexity of “mood” should not dissuade us from carefully investigating users’ preferences in this regard. Adding to the existing efforts of classifying moods conducted by experts, the current study presents mood terms provided by actual end-users when describing different moods in fiction. This study offers a useful roadmap for creating taxonomies for retrieval and description, as well as structures derived from user-provided terms that ultimately have the potential to improve user experience

Web collaboration for software engineering

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 200

Searching for music: understanding the discovery, acquisition, processing and organization of music in a domestic setting for design

This series of studies make it clear that a wide range of both physical and digital resources are involved in domestic music consumption. The selection of digital resources is particularly evident, and it can be observed that domestic music consumption is a fragmented business, taking advantage of many different "channels'' for getting, using and preparing music. While there are not a series of common channels, each home displayed a variety of methods in respect to using metadata in multiple different modalities: regardless, the activities involved in getting, using and preparing music cohere through a noticeable, emergent set of workflows. We find that not only does metadata support searching, as one might expect, but also it pervades all parts of the workflow and is used in real-time as a reflexive artifact and in terms of its future perceived/prescribed use. The findings of the research raise a series of possibilities and issues that form the basis for understanding and designing for metadata use

Characterizing and Evaluating Users' Information Seeking Behavior in Social Tagging Systems

Social tagging systems in the Web 2.0 era present an innovative information seeking environment succeeding the library and traditional Web. The primary goals of this study were to, in this particular context: (1) identify the general information seeking strategies adopted by users and determine their effectiveness; (2) reveals the characteristics of the users who prefer different strategies; and (3) identify the specific traits of users' information seeking paths and understand factors shaping them. A representative social tagging system, Douban (http://www.douban.com/) was chosen as the research setting in order to generate empirical findings.Based on the mixed methods research design, this study consists of a quantitative phase and a qualitative phase. The former firstly involved a clickstream data analysis of 20 million clickstream records requested from Douban at the footprint, movement, and track levels. Limited to studying physical behavior, it was complemented by an online survey which captured Douban users' background information from various aspects. In the subsequent qualitative phase, a focus group gathered a number of experienced Douban users to help interpret the quantitative results.Major findings of this study show that: (1) the general strategies include encountering, browsing by resource, browsing by tag, browsing by user/group, searching, and monitoring by user/group; (2) while browsing by resource is the most popular strategy, browsing by tag is the most effective one; (3) users preferring different strategies do not have significantly different characteristics; and (4) on users' information seeking paths these exist two resource viewing patterns - continuous and sporadic, and two resource collecting patterns - lagged and instant, and they can be attributed to user, task, and system factors.A model was developed to illustrate the strategic and tactic layers of users' information seeking behavior in social tagging systems. It offers a deep insight into the behavioral changes brought about by this new environment as compared to the Web in general. This model can serve as the theoretical base for designing user-oriented information seeking interfaces for social tagging systems so that the general strategies and specific tactics will be accommodated efficiently

From social tagging to polyrepresentation: a study of expert annotating behavior of moving images

Mención Internacional en el título de doctorThis thesis investigates “nichesourcing” (De Boer, Hildebrand, et al., 2012), an emergent initiative of cultural heritage crowdsoucing in which niches of experts are involved in the annotating tasks. This initiative is studied in relation to moving image annotation, and in the context of audiovisual heritage, more specifically, within the sector of film archives. The work presents a case study of film and media scholars to investigate the types of annotations and attribute descriptions that they could eventually contribute, as well as the information needs, and seeking and searching behaviors of this group, in order to determine what the role of the different types of annotations in supporting their expert tasks would be. The study is composed of three independent but interconnected studies using a mixed methodology and an interpretive approach. It uses concepts from the information behavior discipline, and the "Integrated Information Seeking and Retrieval Framework" (IS&R) (Ingwersen and Järvelin, 2005) as guidance for the investigation. The findings show that there are several types of annotations that moving image experts could contribute to a nichesourcing initiative, of which time-based tags are only one of the possibilities. The findings also indicate that for the different foci in film and media research, in-depth indexing at the content level is only needed for supporting a specific research focus, for supporting research in other domains, or for engaging broader audiences. The main implications at the level of information infrastructure are the requirement for more varied annotating support, more interoperability among existing metadata standards and frameworks, and the need for guidelines about crowdsoucing and nichesourcing implementation in the audiovisual heritage sector. This research presents contributions to the studies of social tagging applied to moving images, to the discipline of information behavior, by proposing new concepts related to the area of use behavior, and to the concept of “polyrepresentation” (Ingwersen, 1992, 1996) applied to the humanities domain.Esta tesis investiga la iniciativa del nichesourcing (De Boer, Hildebrand, et al., 2012), como una forma de crowdsoucing en sector del patrimonio cultural, en la cuál grupos de expertos participan en las tareas de anotación de las colecciones. El ámbito de aplicación es la anotación de las imágenes en movimiento en el contexto del patrimonio audiovisual, más específicamente, en el caso de los archivos fílmicos. El trabajo presenta un estudio de caso aplicado a un dominio específico de expertos en el ámbito audiovisual: los académicos de cine y medios. El análisis se centra en dos aspectos específicos del problema: los tipos de anotaciones y atributos en las descripciones que podrían obtenerse de este nicho de expertos; y en las necesidades de información y el comportamiento informacional de dicho grupo, con el fin de determinar cuál es el rol de los diferentes tipos de anotaciones en sus tareas de investigación. La tesis se compone de tres estudios independientes e interconectados; se usa una metodología mixta e interpretativa. El marco teórico se compone de conceptos del área de estudios de comportamiento informacional (“information behavior”) y del “Marco integrado de búsqueda y recuperación de la información” ("Integrated Information Seeking and Retrieval Framework" (IS&R)) propuesto por Ingwersen y Järvelin (2005), que sirven de guía para la investigación. Los hallazgos indican que existen diversas formas de anotación de la imagen en movimiento que podrían generarse a partir de las contribuciones de expertos, de las cuáles las etiquetas a nivel de plano son sólo una de las posibilidades. Igualmente, se identificaron diversos focos de investigación en el área académica de cine y medios. La indexación detallada de contenidos sólo es requerida por uno de esos grupos y por investigadores de otras disciplinas, o como forma de involucrar audiencias más amplias. Las implicaciones más relevantes, a nivel de la infraestructura informacional, se refieren a los requisitos de soporte a formas más variadas de anotación, el requisito de mayor interoperabilidad de los estándares y marcos de metadatos, y la necesidad de publicación de guías de buenas prácticas sobre de cómo implementar iniciativas de crowdsoucing o nichesourcing en el sector del patrimonio audiovisual. Este trabajo presenta aportes a la investigación sobre el etiquetado social aplicado a las imágenes en movimiento, a la disciplina de estudios del comportamiento informacional, a la que se proponen nuevos conceptos relacionados con el área de uso de la información, y al concepto de “poli-representación” (Ingwersen, 1992, 1996) en las disciplinas humanísticas.Programa Oficial de Doctorado en Documentación: Archivos y Bibliotecas en el Entorno DigitalPresidente: Peter Emil Rerup Ingwersen.- Secretario: Antonio Hernández Pérez.- Vocal: Nils Phar

#MPLP: a Comparison of Domain Novice and Expert User-generated Tags in a Minimally Processed Digital Archive

The high costs of creating and maintaining digital archives precluded many archives from providing users with digital content or increasing the amount of digitized materials. Studies have shown users increasingly demand immediate online access to archival materials with detailed descriptions (access points). The adoption of minimal processing to digital archives limits the access points at the folder or series level rather than the item-level description users\u27 desire. User-generated content such as tags, could supplement the minimally processed metadata, though users are reluctant to trust or use unmediated tags. This dissertation project explores the potential for controlling/mediating the supplemental metadata from user-generated tags through inclusion of only expert domain user-generated tags. The study was designed to answer three research questions with two parts each: 1(a) What are the similarities and differences between tags generated by expert and novice users in a minimally processed digital archive?, 1(b) Are there differences between expert and novice users\u27 opinions of the tagging experience and tag creation considerations?, 2(a) In what ways do tags generated by expert and/or novice users in a minimally processed collection correspond with metadata in a traditionally processed digital archive?, 2(b) Does user knowledge affect the proportion of tags matching unselected metadata in a minimally processed digital archive?, 3(a) In what ways do tags generated by expert and/or novice users in a minimally processed collection correspond with existing users\u27 search terms in a digital archive?, and 3(b) Does user knowledge affect the proportion of tags matching query terms in a minimally processed digital archive? The dissertation project was a mixed-methods, quasi-experimental design focused on tag generation within a sample minimally processed digital archive. The study used a sample collection of fifteen documents and fifteen photographs. Sixty participants divided into two groups (novices and experts) based on assessed prior knowledge of the sample collection\u27s domain generated tags for fifteen documents and fifteen photographs (a minimum of one tag per object). Participants completed a pre-questionnaire identifying prior knowledge, and use of social tagging and archives. Additionally, participants provided their opinions regarding factors associated with tagging including the tagging experience and considerations while creating tags through structured and open-ended questions in a post-questionnaire. An open-coding analysis of the created tags developed a coding scheme of six major categories and six subcategories. Application of the coding scheme categorized all generated tags. Additional descriptive statistics summarized the number of tags created by each domain group (expert, novice) for all objects and divided by format (photograph, document). T-tests and Chi-square tests explored the associations (and associative strengths) between domain knowledge and the number of tags created or types of tags created for all objects and divided by format. The subsequent analysis compared the tags with the metadata from the existing collection not displayed within the sample collection participants used. Descriptive statistics summarized the proportion of tags matching unselected metadata and Chi-square tests analyzed the findings for associations with domain knowledge. Finally, the author extracted existing users\u27 query terms from one month of server-log data and compared the generated-tags and unselected metadata. Descriptive statistics summarized the proportion of tags and unselected metadata matching query terms, and Chi-square tests analyzed the findings for associations with domain knowledge. Based on the findings, the author discussed the theoretical and practical implications of including social tags within a minimally processed digital archive