Learning sentiment classification model from labeled features

We propose a novel framework where an initial classifier is learned by incorporating prior information extracted from an existing sentiment lexicon. Preferences on expectations of sentiment labels of those lexicon words are expressed using generalized expectation criteria. Documents classified with high confidence are then used as pseudo-labeled examples for automatical domain-specific feature acquisition. The word-class distributions of such self-learned features are estimated from the pseudo-labeled examples and are used to train another classifier by constraining the model's predictions on unlabeled instances. Experiments on both the movie review data and the multi-domain sentiment dataset show that our approach attains comparable or better performance than exiting weakly-supervised sentiment classification methods despite using no labeled documents.

A novel framework of training hidden Markov support vector machines from lightly-annotated data

Natural language understanding (NLU) aims to map sentences to their semantic mean representations. Statistical approaches to NLU normally require fully-annotated training data where each sentence is paired with its word-level semantic annotations. In this paper, we propose a novel learning framework which trains the Hidden Markov Support Vector Machines (HM-SVMs) without the use of expensive fully-annotated data. In particular, our learning approach takes as input a training set of sentences labeled with abstract semantic annotations encoding underlying embedded structural relations and automatically induces derivation rules that map sentences to their semantic meaning representations. The proposed approach has been tested on the DARPA Communicator Data and achieved 93.18% in F-measure, which outperforms the previously proposed approaches of training the hidden vector state model or conditional random fields from unaligned data, with a relative error reduction rate of 43.3% and 10.6% being achieved.

Joint sentiment/topic model for sentiment analysis

Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework based on Latent Dirichlet Allocation (LDA), called joint sentiment/topic model (JST), which detects sentiment and topic simultaneously from text. Unlike other machine learning approaches to sentiment classification which often require labeled corpora for classifier training, the proposed JST model is fully unsupervised. The model has been evaluated on the movie review dataset to classify the review sentiment polarity and minimum prior information have also been explored to further improve the sentiment classification accuracy. Preliminary experiments have shown promising results achieved by JST.

Originator or propagator? Incorporating social role theory into topic models for twitter content analysis

A large number of studies have been devoted to modeling the contents and interactions between users on Twitter. In this paper, we propose a method inspired from Social Role Theory (SRT), which assumes that a user behaves differently in different roles in the generation process of Twitter content. We consider the two most distinctive social roles on Twitter: originator and propagator, who respectively posts original messages and retweets or forwards the messages from others. In addition, we also consider role-specific social interactions, especially implicit interactions between users who share some common interests. All the above elements are integrated into a novel regularized topic model. We evaluate the proposed method on real Twitter data. The results show that our method is more effective than the existing ones which do not distinguish social roles. Copyright 2013 ACM.

Auditoría integrada de Información + Conocimiento: aplicación en un caso de estudio

Se presentan los resultados de la aplicación de una metodología integradora de auditoría de información y conocimiento, llevada a cabo en un Centro de Investigación del Ministerio de Ciencia, Tecnología y Medio Ambiente de la provincia de Holguín, Cuba, conformada por siete etapas con un enfoque híbrido dirigida a revisar la estrategia y la política de gestión de información y conocimiento, identificar e inventariar y mapear los recursos de I+C y sus flujos, y valorar los procesos asociados a su gestión. La alta dirección de este centro, sus especialistas e investigadores manifestaron la efectividad de la metodología aplicada cuyos resultados propiciaron reajustar la proyección estratégica en relación con la gestión de la I+C, rediseñar los flujos informativos de los procesos claves, disponer de un directorio de sus expertos por áreas y planificar el futuro aprendizaje y desarrollo profesional.

Sistemas curriculares para la gestión de información y conocimiento institucional. Estudio de caso

La organización del conocimiento en el contexto de las Ciencias de la Información tiene como esencia la información y el conocimiento debidamente documentado o registrado. La organización del conocimiento como proceso, envuelve tanto la descripción física como de los contenidos de los objetos informacionales. Y el producto de ese proceso descriptivo es la representación de los atributos de un objeto o conjunto de objetos. Las representaciones son construidas por lenguajes elaborados específicamente para los objetivos de la organización en los sistemas de información. Lenguajes que se subdividen en lenguajes que describen el documento (el soporte físico del objeto) y lenguajes que describen la información (los contenidos).A partir de esta premisa la siguiente investigación tiene como objetivo general analizarlos sistemas de Gestión de Información y Conocimiento Institucional principalmente los que proponen utilizar el Currículum Vitae del profesor como única fuente de información, medición y representación de la información y el conocimiento de una organización. Dentro delos principales resultados se muestra la importancia de usar el currículo personal como fuente de información confiable y normalizada; una síntesis de los principales sistemas curriculares que existen a nivel internacional y regional; así como el gráfico del modelo de datos del caso de estudio; y por último, la propuesta del uso de las ontologías como principal herramienta para la organización semántica de la información en un sistema de gestión de información y conocimiento.

Evaluating Document Retrieval Methods for Resource Selection in Clustered P2P IR

Resource Selection (or Query Routing) is an important step in P2P IR. Though analogous to document retrieval in the sense of choosing a relevant subset of resources, resource selection methods have evolved independently from those for document retrieval. Among the reasons for such divergence is that document retrieval targets scenarios where underlying resources are semantically homogeneous, whereas peers would manage diverse content. We observe that semantic heterogeneity is mitigated in the clustered 2-tier P2P IR architecture resource selection layer by way of usage of clustering, and posit that this necessitates a re-look at the applicability of document retrieval methods for resource selection within such a framework. This paper empirically benchmarks document retrieval models against the state-of-the-art resource selection models for the problem of resource selection in the clustered P2P IR architecture, using classical IR evaluation metrics. Our benchmarking study illustrates that document retrieval models significantly outperform other methods for the task of resource selection in the clustered P2P IR architecture. This indicates that clustered P2P IR framework can exploit advancements in document retrieval methods to deliver corresponding improvements in resource selection, indicating potential convergence of these fields for the clustered P2P IR architecture.

Gestão da Informação e Gestão do Conhecimento: análise das publicações do grupo de trabalho 4 no Encontro Nacional de Pesquisa em Ciência da Informação 2005-2014

Este estudo se baseia em duas áreas afins, a área da Gestão da Informação (GI) que busca gerir a informação registrada e a Gestão do Conhecimento (GC) que procura formas de gerir o capital intelectual dos indivíduos. Na busca por compreender sobre as duas áreas do conhecimento, procurou-se analisar os trabalhos presentes no Grupo de Trabalho 4 do Encontro Nacional de Pesquisa em Pós-Graduação em Ciência da Informação (ENANCIB). Devido a este fato, o presente trabalho tem por objetivo principal investigar como a Gestão da Informação e Gestão do Conhecimento são abordadas nos trabalhos apresentados no ENANCIB, tendo por objetivos específicos identificar os trabalhos sobre GI e GC do GT4, a análise de autoria e co-autoria presente nos mesmo, realizar a averiguação das palavras-chave utilizadas, e a investigação de aspectos de abordagem da GI e GC. Para a consecução dos objetivos foi utilizado o método exploratório-descritivo, pois foi realizada a descrições dos contextos dos trabalhos para descobrir as relações existentes entre seus componentes. Como resultado, conclui-se que embora a GI e a GC sejam abordadas em muitos trabalhos, há muitos trabalhos no qual não se é possível ter uma identificação sobre a abordagem de ambas as áreas. Quanto à autoria dos trabalhos, Marta L. P. Valentim é a autora com maior número de apresentações por evento, no que tange a co-autoria há a predominância de dois autores por trabalho. No que se relaciona as palavras-chave encontradas nos trabalhos, observou que a palavra mais comum é GI. E os aspectos em que GI e GC são abordadas são variados, salientando a sua forte presença em organizações.

Gestão de Informação e do Conhecimento

Nos últimos anos, a Gestão de Informação e do Conhecimento (GIC) tem despertado um interesse cada vez maior por parte da comunidade científica e de prestigiadas organizações empresariais e governamentais. A incorporação organizacional desta disciplina possibilitou a correção de lacunas de informação e de conhecimento, contribuindo eficazmente para a superioridade de informação. Desta maneira, este estudo tem por objetivo determinar as opções que permitirão ao Exército Português maximizar a sua eficácia no âmbito da GIC. Posto isto, analisar-se-á primeiramente o impacto da “era da informação” na atual gestão organizacional. Em seguida, proceder-se-á à avaliação do modelo de GIC que melhor servirá uma organização tipo Exército Português, verificando-se, numa fase final, quais os aspetos que caracterizam o atual modelo em vigor no Exército e qual o seu impacto na sua gestão estratégica. Por último, conclui-se com o presente estudo que se encontra em curso uma transformação ao nível de toda a cultura organizacional do Exército, uma vez que a mesma passa a centralizar o seu processo de decisão em rede. Para isso, torna-se essencial a implementação eficaz da GIC, o que é apenas é praticável com a definição de uma estratégia e de um plano de ação para a sua eficaz materialização. Abstract: The Information and Knowledge Management (IKM) is beginning to awaken a growing interest in the academic world as well as in large organizations globally. The implementation of this type of capability allows bridging the information and knowledge gaps contributing to achieve in organizational terms the information superiority. This study focuses on determining the options that will allow the Portuguese Army in order to maximize its effectiveness within the IKM. To achieve this purpose, it begins by analyzing how the "information age" influences the management of organizations. Next, we evaluate which model of IKM that could best serve an organization like the Portuguese Army and finally we analyze which aspects characterizing the current IKM model in the Army and its impact on its Strategic Management. We conclude that the Army is crossing a transformation of the whole organizational culture passing this to centralize its decision process through the network changing the whole paradigm of sharing and obligation to share. For this, it is essential to the implementation of the IKM capacity and this is only possible with the definition of a strategy and action plan for the implementation of this strategy.

Informationen verzweifelt gesucht – Enterprise Search in österreichischen Großunternehmen

Die Arbeit geht dem Status quo der unternehmensweiten Suche in österreichischen Großunternehmen nach und beleuchtet Faktoren, die darauf Einfluss haben. Aus der Analyse des Ist-Zustands wird der Bedarf an Enterprise-Search-Software abgeleitet und es werden Rahmenbedingungen für deren erfolgreiche Einführung skizziert. Die Untersuchung stützt sich auf eine im Jahr 2009 durchgeführte Onlinebefragung von 469 österreichischen Großunternehmen (Rücklauf 22 %) und daran anschließende Leitfadeninterviews mit zwölf Teilnehmern der Onlinebefragung. Der theoretische Teil verortet die Arbeit im Kontext des Informations- und Wissensmanagements. Der Fokus liegt auf dem Ansatz der Enterprise Search, ihrer Abgrenzung gegenüber der Suche im Internet und ihrem Leistungsspektrum. Im empirischen Teil wird zunächst aufgezeigt, wie die Unternehmen ihre Informationen organisieren und welche Probleme dabei auftreten. Es folgt eine Analyse des Status quo der Informationssuche im Unternehmen. Abschließend werden Bekanntheit und Einsatz von Enterprise-Search-Software in der Zielgruppe untersucht sowie für die Einführung dieser Software nötige Rahmenbedingungen benannt. Defizite machen die Befragten insbesondere im Hinblick auf die übergreifende Suche im Unternehmen und die Suche nach Kompetenzträgern aus. Hier werden Lücken im Wissensmanagement offenbar. 29 % der Respondenten der Onlinebefragung geben zudem an, dass es in ihren Unternehmen gelegentlich bis häufig zu Fehlentscheidungen infolge defizitärer Informationslagen kommt. Enterprise-Search-Software kommt in 17 % der Unternehmen, die sich an der Onlinebefragung beteiligten, zum Einsatz. Die durch Enterprise-Search-Software bewirkten Veränderungen werden grundsätzlich positiv beurteilt. Alles in allem zeigen die Ergebnisse, dass Enterprise-Search-Strategien nur Erfolg haben können, wenn man sie in umfassende Maßnahmen des Informations- und Wissensmanagements einbettet.

Enterprise information portals: potential for evaluating research for knowledge management and human capital assets using social network analysis

Paper presented at the ECKM 2010 – 11th European Conference on Knowledge Management, 2-3 September, 2010, Famalicão, Portugal. URL: http://www.academic-conferences.org/eckm/eckm2010/eckm10-home.htm

Knowledge Management and Information Systems based on Workflow Technology

Knowledge management is critical for the success of virtual communities, especially in the case of distributed working groups. A representative example of this scenario is the distributed software development, where it is necessary an optimal coordination to avoid common problems such as duplicated work. In this paper the feasibility of using the workflow technology as a knowledge management system is discussed, and a practical use case is presented. This use case is an information system that has been deployed within a banking environment. It combines common workflow technology with a new conception of the interaction among participants through the extension of existing definition languages.