Semantic contextualisation of social tag-based profiles and item recommendations

Proceedigns of 12th International Conference, EC-Web 2011, Toulouse, France, August 30 - September 1, 2011.The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-23014-1_9We present an approach that efficiently identifies the semantic meanings and contexts of social tags within a particular folksonomy, and exploits them to build contextualised tag-based user and item profiles. We apply our approach to a dataset obtained from Delicious social bookmarking system, and evaluate it through two experiments: a user study consisting of manual judgements of tag disambiguation and contextualisation cases, and an offline study measuring the performance of several tag-powered item recommendation algorithms by using contextualised profiles. The results obtained show that our approach is able to accurately determine the actual semantic meanings and contexts of tag annotations, and allow item recommenders to achieve better precision and recall on their predictions.This work was supported by the Spanish Ministry of Science and Innovation (TIN2008-06566-C04-02), and the Community of Madrid (CCG10- UAM/TIC-5877

Content-based recommendation in social tagging systems

This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in RecSys '10 Proceedings of the fourth ACM conference on Recommender systems , http://dx.doi.org/10.1145/10.1145/1864708.1864756.In a general collaborative filtering (CF) setting, a user profile contains a set of previously rated items and is used to represent the user's interest. Unfortunately, most CF approaches ignore the underlying structure of user profiles. In this paper, we argue that a certain class of interest is best represented jointly by several items, drawing an analogy to "phrases" in text retrieval, which are not equivalent to the separate meaning of their words. At an alternative stance, we also consider the situation where, analogously to word synonyms, two items might be substitutable when representing a class of interest. We propose an approach integrating these two notions as opposing poles on a continuum spectrum. Upon this, we model the underlying structure in user profiles, drawing an analogy with text retrieval. The approach gives rise to a novel structured Vector Space Model for CF. We show that item-based CF approaches are a special case of the proposed method

A Survey on Personalized Recommendation Techniques

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La rentabilidad en inversión social media: el roi y su cálculo

En la actualidad, muchas empresas se han interesado en entrar en el mundo de las redes sociales por los beneficios que pueden suponer para ellas, pero desconocen como cuantificar monetariamente dichos objetivos. Con este Trabajo de Fin de Grado nos proponemos ver cuáles son las mejores maneras para computarlo y las fórmulas más correctas a la hora de calcularlo. En épocas anteriores, las empresas ni siquiera se planteaban el operar online: la presencia de Internet en este país era escasa. Pero con el paso de los años, Internet ha entrado en los hogares de la mayoría de las familias españolas y es cada vez más natural comprar online y relacionarnos en la red, tanto con amigos como con empresas. Estas últimas tienen que luchar por entrar también en el círculo social del usuario, convertirse en “su amigo”, ya que esto le reportará un beneficio inigualable que necesitaría una gran inversión si se intentara conseguir por otros medios tradicionales. Pero, el problema radica en que las empresas desconocen cómo cuantificar este beneficio. A pesar de que parezca casi imposible calcular algo tan intangible como el valor de un “like”1 de Facebook o de un “Retweet”2 de Twitter, comprobaremos que a partir de teorías sencillas y métricas poco complejas podemos llegar a estos resultados tan interesantes para la empresa actual Nos basamos en una revisión de publicaciones, artículos y obras de varios expertos en el tema para tratar el tema del cálculo del ROI dentro de las redes sociales, acompañándolo de una parte práctica en la que se desarrollan las diferentes fórmulas expuestas.Facultad de Ciencias de la EmpresaUniversidad Politécnica de Cartagen

Social search : application, possibilities and challenges

Razvoj društvenih medija i weba 2.0. omogućio je iskorištavanje društveno stvorenog sadržaja kako bi se poboljšali rezultati pretraživanja. U radu se prikazuju mogućnosti primjene društvenog pretraživanja, njegove prednosti i nedostaci. Cilj je pokušati odgovoriti na pitanje da li se društveno pretraživanje može uspješno koristiti kao nadopuna tradicionalnom pretraživanju. Tradicionalno pretraživanje često ostavlja korisnike nezadovoljnima jer nisu uspjeli pronaći odgovor na svoju informacijsku potrebu. Nekada se to događa zbog samih korisnika koji ne znaju pravilno oblikovati svoju potrebu u upit, a nekada zbog toga što pretraživači zanemaruju kontekst pretraživanja i specifične potrebe pojedinog korisnika. Društveno pretraživanje pokušava razriješiti oba navedena problema. U prvom je dijelu rada opisan pojam pretraživanja informacija i objašnjen način na kojem funkcionira tradicionalno pretraživanje. Navedene su vrste modela pretraživanja, korisničkih upita i podjela korisnika prema stručnosti pretraživanja, te su analizirani utjecaji koje je razvoj World Wide Weba imao na pretraživanje informacija. U drugom dijelu rada prikazane su različite primjene društvenog pretraživanja, a kroz primjere objašnjen je način njihovog funkcioniranja i arhitektura sustava.Social Media and development of Web 2.0. made it possible to make use of sociallygenerated content to improve search results. The paper presents the possibilities of social search, its advantages and disadvantages. The goal is to try to answer whether social search can be successfully used to complement traditional search. Traditional search often leaves users dissatisfied because they have been unable to find an answer to their information need. Sometimes this happens because the users do not know how to properly convey their need into query, and sometimes because search engines ignore the search context and specific needs of the individual user. Social search is trying to solve both of these problems. The first part of the paper describes the concept of information retrieval and explains how traditional search works. Types of search models, user queries, and user taxonomy are listed, and the impacts that the development of the World Wide Web has had on information retrieval have been analyzed. In the second part of the paper, various applications of social search are presented, and through the examples system architecture and the way they function is explained

Exploring online social activities for adaptive search personalization

The web has largely become a very social environment and will continue to become even more so. People are not only enjoying their social visibility on the Web but also increasingly participating in various social activities delivered through the Web. In this paper, we propose to explore a user’s public social activities, such as blog-ging and social bookmarking, to personalize Internet services. We believe that public social data provides a more acceptable way to derive user interests than more private data such as search histories and desktop data. We propose a framework that learns about users’ preferences from their activities on a variety of online social sys-tems. As an example, we illustrate how to apply the user interests derived by our system to personalize search results. Furthermore, our system is adaptive; it observes users ’ choices on search results and automatically adjusts the weights of different social systems during the information integration process, so as to refine its in-terest profile for each user. We have implemented our approach and performed experiments on real-world data collected from three large-scale online social systems. Over two hundred users from worldwide who are active on the three social systems have been tested. Our experimental results demonstrate the effectiveness of our personalized search approach. Our results also show that inte-grating information from multiple social systems usually leads to better personalized results than relying on the information from a single social system, and our adaptive approach further improves the performance of the personalization solution

Social Media Marketing Plan for a Furniture Company in Chinese Market : Case Company: Company X

In the information era, the internet has affected people’s lives in many aspects. In addition to spreading information and sharing resources, the internet has also affected companies’ marketing approaches. The marketing focus has been slowly shifted from traditional marketing to digital marketing. Social media marketing, the most representative one among which, has brought new possibilities and opportunities for marketers. The aim of the thesis is to explain the concepts of social media marketing and customer behavior. The final goal is to develop a plan for the case company to reach its target segment in China. A deductive research approach is applied in the thesis. Both qualitative and quantitative research methods are used for data collection. Qualitative research is conducted through an interview with the marketing manager of the case company and quantitative research is implemented through a survey. The authors collect data from both primary and secondary sources. Secondary data is collected from reliable resources like published journals, books and from the internet. Primary data is collected from the interview with the marketing manager and a survey. In the theoretical part, the authors introduce several marketing concepts such as the five-step marketing process, concepts of online marketing domains and social media marketing in the western world. Then theories of customers’ decision-making process are introduced for understanding the customers better. Also, social media marketing in China is covered and social media radar is presented. With the assist of SWOT-analysis, the authors conduct a development plan for the case company. The main result indicates that the case company should focus more on social media through creating new channels and improve performances. By using social media platforms efficiently, the case company could not only attract new customer but also gain customer loyalty