Nowadays, the effective management of information is extremely important for all spheres of our lives and applications such as search engines and question answering systems help users to find the information that they need. However, even when assisted by these various applications, people sometimes struggle to find what they want. For example, when choosing a product customers can be confused by the need to consider many features before they can reach a decision. Interactive question answering (IQA) systems can help customers in this process, by answering questions about products and initiating a dialogue with the customers when their needs are not clearly defined. The focus of this thesis is how to design an interactive question answering system that will assist users in choosing a product they are looking for, in an optimal way, when a large number of similar products are available. Such an IQA system will be based on selecting a set of characteristics (also referred to as product features in this thesis), that describe the relevant product, and narrowing the search space. We believe that the order in which these characteristics are presented in terms of these IQA sessions is of high importance. Therefore, they need to be ranked in order to have a dialogue which selects the product in an efficient manner. The research question investigated in this thesis is whether product characteristics mentioned in user reviews are important for a person who is likely to purchase a product and can therefore be used when designing an IQA system. We focus our attention on products such as mobile phones; however, the proposed techniques can be adapted for other types of products if the data is available. Methods from natural language processing (NLP) fields such as coreference resolution, relation extraction and opinion mining are combined to produce various rankings of phone features. The research presented in this thesis employs two corpora which contain texts related to mobile phones specifically collected for this thesis: a corpus of Wikipedia articles about mobile phones and a corpus of mobile phone reviews published on the Epinions.com website. Parts of these corpora were manually annotated with coreference relations, mobile phone features and relations between mentions of the phone and its features. The annotation is used to develop a coreference resolution module as well as a machine learning-based relation extractor. Rule-based methods for identification of coreference chains describing the phone are designed and thoroughly evaluated against the annotated gold standard. Machine learning is used to find links between mentions of the phone (identified by coreference resolution) and phone features. It determines whether some phone feature belong to the phone mentioned in the same sentence or not. In order to find the best rankings, this thesis investigates several settings. One of the hypotheses tested here is that the relatively low results of the proposed baseline are caused by noise introduced by sentences which are not directly related to the phone and phone feature. To test this hypothesis, only sentences which contained mentions of the mobile phone and a phone feature linked to it were processed to produce rankings of the phones features. Selection of the relevant sentences is based on the results of coreference resolution and relation extraction. Another hypothesis is that opinionated sentences are a good source for ranking the phone features. In order to investigate this, a sentiment classification system is also employed to distinguish between features mentioned in positive and negative contexts. The detailed evaluation and error analysis of the methods proposed form an important part of this research and ensure that the results provided in this thesis are reliable.

Made available in DSpace on 2016-04-27T18:47:16Z (GMT). No. of bitstreams: 1 Thuam Silva Rodrigues.pdf: 3670437 bytes, checksum: 4c386feb686d5ac4a5ad6d0237d098c6 (MD5) Previous issue date: 2015-02-10 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The relation between aging and religion is currently being more widespread in the scientific and academic literature, the religion would be, to the human been, a parameter of conducts organization, and interpretation of experience in different situations of confrotation to life conditions, in any culture and in many age groups, which fact would help positively experience the aging and old age process. The demographics data show dynamic displacement of people among the various religious groups in the country, for example Seicho no le, which has been protuding specially for being constituted by brazilian non-oriental more than Japonese immigrant descendents. However, this religion change only will happen fully if held in symbolic. The symbolic transits to the alterity, difference and metaphor and produces a new sense. Lastly, the religions are constituted as symbolic capital sources, giving sense to the new experiences. The research methodologhy, to undestand the reality of the narratives of the individuals was applied the tools of qualitative and quantitative research (semi-structured questionnaire), with the elders, using the technique of the recorder. Was selected 15 people, the inclusion of this individuals was according to the following criteria: sixty years or aged superior, of both sexes, who migrated from one religion to the Seicho no Ie, and participate there more than a year. The quantitative data analysis was obtained through the data treatment by software Statiscal Packet Social Science SPSS 11.0 for Windows. The qualitative data was analysed, following two phase: analisys of data to identify the categories that enhance and then perform the descriptive interpretation based on the analysis of the literature results. The results analisys showed that the main factor of migration of elders to Seicho no Ie was through the sense of healing and solutions to family problems, an original way and with its own fascination of symbolic universe able to convince people on the treatment of the disease. Although the elders claim perform the Seicho no Ie rituals, they keep the catolicism as symbolic core, everyone state perform prayers and catolicism rituals. In other words, there is not a conversion of a catholic person to Seicho no le but a religious duplicity, in which there is a new interpretation or symbolic system increase, enabling acceptance to the symbolic of Seicho no Ie, we can observe the intense dedication to Seicho no Ie rituals, and low frequency to Catholic rituals. About the meaning of Seicho no Ie, for the elderly, the vast majority defines the Seicho no Ie as a religion and filosifia that teaches them how to live better / A relação envelhecimento e religião vem sendo atualmente mais difundida na literatura científica e acadêmica, a religião seria para ser humano, um parâmetro, de organização de condutas, e interpretação de experiência, em situações distintas de enfrentamento das condições da vida, em qualquer cultura, e em todas as faixas etárias, o que ajudaria de forma positiva vivenciar o processo de envelhecimento e velhice. Os dados demográficos evidenciam dinâmicas de deslocamento de pessoas entre os diversos grupos religiosos existentes no país, dentre elas a Seicho no Ie, que se destaca precisamente em razão de constituir muito mais de adeptos brasileiros não-orientais do que de descendentes de imigrantes japoneses. Porém, esta mudança de religião só se efetuará plenamente se for realizada no simbólico. O simbólico transita pela alteridade, pela diferença e pela metáfora, e produz um novo sentido. As religiões se constituem, antes de tudo, como fontes de capital simbólico, dando sentido às novas experiências. A metodologia da pesquisa leva em conta tanto a análise quantitativa quanto a qualitativa (questionário semiestruturado). Foram selecionados 15 sujeitos. A inclusão dos sujeitos obedeceu aos seguintes critérios: idade igual ou superior a 60 anos, de ambos os sexos, que migraram de uma religião para a Seicho no Ie, e participam na mesma há mais de um ano. Da análise dos dados quantitativos foi obtido o perfil sociodemográfico dos adeptos. Os dados qualitativos foram analisados, seguindo duas fases: primeira, para identificar nas narrativas as categorias que se destacam; segunda, para realizar a interpretação descritiva com base na literatura. Os resultados demonstraram que o principal fator de migração dos idosos para Seicho no Ie foi o sentido de cura e soluções de problemas familiares, que se deu de uma forma original, por meio do fascínio, próprio do universo simbólico, capaz de convencer as pessoas sobre o tratamento da doença. Embora declarem realizar os rituais da Seicho no Ie, os idosos mantém o catolicismo como um sistema simbólico, todos declararam também realizar orações e rituais do catolicismo. A partir da análise destes recortes de narrativas, não mostramos a conversão de uma pessoa da Igreja Católica para a Seicho no Ie, e sim uma duplicidade religiosa. Se fizermos uma nova interpretação ou se acrescentarmos à análise o sistema simbólico, verificamos uma maior aceitação ao simbólico da doutrina, expresso por uma intensa dedicação aos ritos da SNI e uma pequena frequência aos rituais católicos. Sobre o significado da Seicho no Ie, para os entrevistados, a grande maioria define a Seicho no Ie como uma religião e filosofia de vida

Macháč, R. Strategic management of gardening and landscaping company. Diploma thesis. Brno: Mendel University in Brno, 2017. The diploma thesis deals with strategic management of the company and its goal is to create variants of strategy and assess the current state of the company STROMMY COMPANY Ltd. and the market in which it operates. The partial aim is to implement strategic management of the company. To analyse the external environment is used PESTE analysis and Porter´s five force analysis. Internal environment is analyzed using a model 7S, analysis of internal resources and financial analysis. Based on the identification and analysis of key success factors there were used IE matrix and SWOT matrix and were formulated strategic recommendations and actions to implement strategic management.

The thesis is focused on the design of corporate strategy for the company AMPO, s.r.o., which is created through the outputs of the strategic analysis and by using methods, tools and models, and should improve the situation of the company and achieve the selected strategic. The author in creating a new strategy for the company AMPO, s.r.o. Used modeling methods and the final outcome was a summary of the recommendations and create a graphical model of the proposed strategy. The literature search focused on the topic of strategy and strategic management. They described various methods, tools and models, which were then used in the practical part and are the basis for the formulation and implementation strategies.

Several real world tasks involve data that is uncertain and relational in nature. Traditional approaches like first-order logic and probabilistic models either deal with structured data or uncertainty, but not both. To address these limitations, statistical relational learning (SRL), a new area in machine learning integrating both first-order logic and probabilistic graphical models, has emerged in the recent past. The advantage of SRL models is that they can handle both uncertainty and structured/relational data. As a result, they are widely used in domains like social network analysis, biological data analysis, and natural language processing. Bayesian Logic Programs (BLPs), which integrate both first-order logic and Bayesian net- works are a powerful SRL formalism developed in the recent past. In this dissertation, we develop approaches using BLPs to solve two real world tasks – plan recognition and machine reading. Plan recognition is the task of predicting an agent’s top-level plans based on its observed actions. It is an abductive reasoning task that involves inferring cause from effect. In the first part of the dissertation, we develop an approach to abductive plan recognition using BLPs. Since BLPs employ logical deduction to construct the networks, they cannot be used effectively for abductive plan recognition as is. Therefore, we extend BLPs to use logical abduction to construct Bayesian networks and call the resulting model Bayesian Abductive Logic Programs (BALPs). In the second part of the dissertation, we apply BLPs to the task of machine reading, which involves automatic extraction of knowledge from natural language text. Most information extraction (IE) systems identify facts that are explicitly stated in text. However, much of the information conveyed in text must be inferred from what is explicitly stated since easily inferable facts are rarely mentioned. Human readers naturally use common sense knowledge and “read between the lines” to infer such implicit information from the explicitly stated facts. Since IE systems do not have access to common sense knowledge, they cannot perform deeper reasoning to infer implicitly stated facts. Here, we first develop an approach using BLPs to infer implicitly stated facts from natural language text. It involves learning uncertain common sense knowledge in the form of probabilistic first-order rules by mining a large corpus of automatically extracted facts using an existing rule learner. These rules are then used to derive additional facts from extracted information using BLP inference. We then develop an online rule learner that handles the concise, incomplete nature of natural-language text and learns first-order rules from noisy IE extractions. Finally, we develop a novel approach to calculate the weights of the rules using a curated lexical ontology like WordNet. Both tasks described above involve inference and learning from partially observed or incomplete data. In plan recognition, the underlying cause or the top-level plan that resulted in the observed actions is not known or observed. Further, only a subset of the executed actions can be observed by the plan recognition system resulting in partially observed data. Similarly, in machine reading, since some information is implicitly stated, they are rarely observed in the data. In this dissertation, we demonstrate the efficacy of BLPs for inference and learning from incomplete data. Experimental comparison on various benchmark data sets on both tasks demonstrate the superior performance of BLPs over state-of-the-art methods. / text

Dans les écoles primaires québécoises, les cours d'arts font partie des domaines d’apprentissage obligatoires. Toutefois, les effets de l’apprentissage des arts sur les jeunes élèves demeurent mal connus puisque d’une part, l'art est fréquemment perçu comme une discipline de deuxième ordre et d’autre part, des programmes à volet artistique voient encore le jour dans certaines écoles. L’objectif de l’étude est de déterminer si les élèves de 4ième, 5ième et 6ième années fréquentant une école à volet artistique développent davantage d'habiletés particulières liées directement à leur intelligence émotionnelle (IE) comparativement à des élèves fréquentant une école à programme régulier. Une méthodologie reposant sur un devis quasi expérimental avec groupe témoin non équivalent est privilégiée. Les scores d’IE ont été mesurés à l’aide de questionnaires complétés par les élèves, leur enseignant ainsi que leurs parents afin de trianguler les données. Dans un premier temps, les résultats obtenus auprès de l’ensemble de l’échantillon montrent que selon la perception des enseignants, les élèves suivant des cours d’art en parascolaire ont une IE plus élevée que les élèves qui n’en suivent pas. Toutefois, la fréquentation d’une école proposant un programme artistique ne semble pas avoir d'incidence sur le développement de l'IE puisque les résultats obtenus dans le cadre de cette étude montrent que les élèves inscrits à une école à vocation artistique ont une IE inférieure à celle des élèves provenant d’un programme régulier. Ces résultats contradictoires à l’hypothèse de départ sont discutés à la lumière de la littérature scientifique disponible, ainsi que des forces et des limites de la présente recherche. / In Quebec’s elementary schools, arts education is compulsory. As a matter of fact, study programs with an artistic concentration are present in many schools. However, some individuals still consider that arts education is a less important field of study. As a result, the effects learning arts has on young students remain unclear. The objective of this study is to determine if students from grades 4, 5 and 6 who study in a school with an artistic program develop more abilities linked to their emotional intelligence (EI), compared to students who study in a school with a regular program. A quasi-experimental research design with a non equivalent control group was used. EI scores were measured with questionnaires completed by students, their teachers and their parents. Using three different types of respondents made it possible to triangulate the data. Results first show that, according to teachers’ perception, students who followed arts courses in extracurricular activities have a higher EI than students who did not follow those kinds of courses. However, participation in an artistic program does not appear to have an effect on the development of EI, because our results indicate that students who attend a school that offers an artistic program have lower EI than students from regular schools. Outcomes are discussed in light of the current literature, and according to the strengths and the weaknesses of the current study.

Entre as áreas que mais se desenvolvem na informática nos últimos anos estão aquelas relacionadas ao crescimento da rede Internet, que interliga milhões de usuários de todo o mundo. Esta rede disponibiliza aos usuários uma a enorme variedade e quantidade de informações, principalmente dados armazenados de forma não estruturada ou semi estruturada. Contudo, tal volume e heterogeneidade acaba dificultando a manipulação dos dados recuperados a partir da Internet. Este problema motivou o desenvolvimento deste trabalho. Mesmo com o auxílio de várias ferramentas de pesquisa na Internet, buscando realizar pesquisas sobre assuntos específicos, o usuário ainda tem que manipular em seu computador pessoal uma grande quantidade de informação, pois estas ferramentas não realizam um processo de seleção detalhado. Ou seja, são recuperados muitos dados não interessantes ao usuário. Existe, também, uma grande diversidade de assuntos e padrões de transferência e armazenamento da informação criando os mais heterogêneos ambientes de pesquisa e consulta de dados. Esta heterogeneidade faz com que o usuário da rede deva conhecer todo um conjunto de padrões e ferramentas a fim de obter a informação desejada. No entanto, a maior dificuldade de manipulação esta ligada aos formatos de armazenamento não estruturados ou pouco estruturados, como, por exemplo: arquivos textos, Mails (correspondência eletrônica) e artigos de News (jornais eletrônicos). Nestes formatos, o entendimento do documento exige a leitura do mesmo pelo usuário, o que muitas vezes acarreta em um gasto de tempo desnecessário, pois o documento, por exemplo, pode não ser de interesse deste ou, então, ser de interesse, mas sua leitura completa só seria útil posteriormente. Várias informações, como chamadas de trabalhos para congressos, preços de produtos e estatísticas econômicas, entre outras, apresentam validade temporal. Outras informações são atualizadas periodicamente. Muitas dessas características temporais são explicitas, outras estão implícitas no meio de outros tipos de dados. Isto torna muito difícil a recuperação de tal tipo de informação, gerando, várias vezes, a utilização de informações desatualizadas, ou a perda de oportunidades. Desta forma, o grande volume de dados em arquivos pessoais obtidos a partir da Internet criou uma complexa tarefa de gerenciamento dos mesmos em conseqüência da natureza não estruturada dos documentos recuperados e da complexidade da análise do tempo de validade inerente a estes dados. Com o objetivo de satisfazer as necessidades de seleção e conseqüente manipulação das informações existentes a nível local (computador pessoal), neste trabalho, é descrito um sistema para extração e sumarização destes dados, utilizando conceitos de IE (Information Extraction) e Sistemas Baseados em Conhecimento. Os dados processados são parcialmente estruturados ou não estruturados, sendo manipulados por um extrator configurado a partir de bases de conhecimento geradas pelo usuário do sistema. O objetivo final desta dissertação é a implementação do Sistema de Extração Semântica de Informações, o qual permite a classificação dos dados extraídos em classes significativas para o usuário e a determinação da validade temporal destes dados a partir da geração de uma base de dados estruturada. / One of the most challenging area in Computer Science is related to Internet technology. This network offers to the users a large variety and amount of information, mainly, data storage in unstructured or semi-structured formats. However, the vast data volume and heterogeneity transforms the retrieved data manipulation a very arduous work. This problem was the prime motivation of this work. As with many tools for data retrieval and specific searching, the user has to manipulate in his personal computer an increasing amount of information, because these tools do not realize a precise data selection process. Many retrieval data are not interesting for the user. There are, also, a big diversity of subjects and standards in information transmission and storage, creating the most heterogeneous environments in data searching and retrieval. Due to this heterogeneity, the user has to know many data standards and searching tools to obtain the requested information. However, the fundamental problem for data manipulation is the partially or fully unstructured data formats, as text, mail and news data structures. For files in these formats, the user has to read each of the files to filter the relevant information, originating a loss of time, because the document could be not interesting for the user, or if it is interesting, its complete reading may be unnecessary at the moment. Some information as call-for-papers, product prices, economic statistics and others, has associated a temporal validity. Other information are updated periodically. Some of these temporal characteristics are explicit, others are implicitly embedded in other data types. As it is very difficult to retrieve the temporal data automatically, which generate, many times, the use of invalid information, as a result, some opportunities are lost. On this paper a system for extraction and summarizing of data is described. The main objective is to satisfy the user's selection needs and consequently information manipulation stored in a personal computer. To achieve this goal we are employed the concepts of Information Extraction (IE) and Knowledge Based Systems. The input data manipulation is done by an extraction procedure configured by a user who defined knowledge base. The objective of this paper is to develop a System of Semantic Extraction of Information which classifies the data extracted in meaningful classes for the user and to deduce the temporal validity of this data. This goal was achieved by the generation of a structured temporal data base.

Entre as áreas que mais se desenvolvem na informática nos últimos anos estão aquelas relacionadas ao crescimento da rede Internet, que interliga milhões de usuários de todo o mundo. Esta rede disponibiliza aos usuários uma a enorme variedade e quantidade de informações, principalmente dados armazenados de forma não estruturada ou semi estruturada. Contudo, tal volume e heterogeneidade acaba dificultando a manipulação dos dados recuperados a partir da Internet. Este problema motivou o desenvolvimento deste trabalho. Mesmo com o auxílio de várias ferramentas de pesquisa na Internet, buscando realizar pesquisas sobre assuntos específicos, o usuário ainda tem que manipular em seu computador pessoal uma grande quantidade de informação, pois estas ferramentas não realizam um processo de seleção detalhado. Ou seja, são recuperados muitos dados não interessantes ao usuário. Existe, também, uma grande diversidade de assuntos e padrões de transferência e armazenamento da informação criando os mais heterogêneos ambientes de pesquisa e consulta de dados. Esta heterogeneidade faz com que o usuário da rede deva conhecer todo um conjunto de padrões e ferramentas a fim de obter a informação desejada. No entanto, a maior dificuldade de manipulação esta ligada aos formatos de armazenamento não estruturados ou pouco estruturados, como, por exemplo: arquivos textos, Mails (correspondência eletrônica) e artigos de News (jornais eletrônicos). Nestes formatos, o entendimento do documento exige a leitura do mesmo pelo usuário, o que muitas vezes acarreta em um gasto de tempo desnecessário, pois o documento, por exemplo, pode não ser de interesse deste ou, então, ser de interesse, mas sua leitura completa só seria útil posteriormente. Várias informações, como chamadas de trabalhos para congressos, preços de produtos e estatísticas econômicas, entre outras, apresentam validade temporal. Outras informações são atualizadas periodicamente. Muitas dessas características temporais são explicitas, outras estão implícitas no meio de outros tipos de dados. Isto torna muito difícil a recuperação de tal tipo de informação, gerando, várias vezes, a utilização de informações desatualizadas, ou a perda de oportunidades. Desta forma, o grande volume de dados em arquivos pessoais obtidos a partir da Internet criou uma complexa tarefa de gerenciamento dos mesmos em conseqüência da natureza não estruturada dos documentos recuperados e da complexidade da análise do tempo de validade inerente a estes dados. Com o objetivo de satisfazer as necessidades de seleção e conseqüente manipulação das informações existentes a nível local (computador pessoal), neste trabalho, é descrito um sistema para extração e sumarização destes dados, utilizando conceitos de IE (Information Extraction) e Sistemas Baseados em Conhecimento. Os dados processados são parcialmente estruturados ou não estruturados, sendo manipulados por um extrator configurado a partir de bases de conhecimento geradas pelo usuário do sistema. O objetivo final desta dissertação é a implementação do Sistema de Extração Semântica de Informações, o qual permite a classificação dos dados extraídos em classes significativas para o usuário e a determinação da validade temporal destes dados a partir da geração de uma base de dados estruturada. / One of the most challenging area in Computer Science is related to Internet technology. This network offers to the users a large variety and amount of information, mainly, data storage in unstructured or semi-structured formats. However, the vast data volume and heterogeneity transforms the retrieved data manipulation a very arduous work. This problem was the prime motivation of this work. As with many tools for data retrieval and specific searching, the user has to manipulate in his personal computer an increasing amount of information, because these tools do not realize a precise data selection process. Many retrieval data are not interesting for the user. There are, also, a big diversity of subjects and standards in information transmission and storage, creating the most heterogeneous environments in data searching and retrieval. Due to this heterogeneity, the user has to know many data standards and searching tools to obtain the requested information. However, the fundamental problem for data manipulation is the partially or fully unstructured data formats, as text, mail and news data structures. For files in these formats, the user has to read each of the files to filter the relevant information, originating a loss of time, because the document could be not interesting for the user, or if it is interesting, its complete reading may be unnecessary at the moment. Some information as call-for-papers, product prices, economic statistics and others, has associated a temporal validity. Other information are updated periodically. Some of these temporal characteristics are explicit, others are implicitly embedded in other data types. As it is very difficult to retrieve the temporal data automatically, which generate, many times, the use of invalid information, as a result, some opportunities are lost. On this paper a system for extraction and summarizing of data is described. The main objective is to satisfy the user's selection needs and consequently information manipulation stored in a personal computer. To achieve this goal we are employed the concepts of Information Extraction (IE) and Knowledge Based Systems. The input data manipulation is done by an extraction procedure configured by a user who defined knowledge base. The objective of this paper is to develop a System of Semantic Extraction of Information which classifies the data extracted in meaningful classes for the user and to deduce the temporal validity of this data. This goal was achieved by the generation of a structured temporal data base.

Entre as áreas que mais se desenvolvem na informática nos últimos anos estão aquelas relacionadas ao crescimento da rede Internet, que interliga milhões de usuários de todo o mundo. Esta rede disponibiliza aos usuários uma a enorme variedade e quantidade de informações, principalmente dados armazenados de forma não estruturada ou semi estruturada. Contudo, tal volume e heterogeneidade acaba dificultando a manipulação dos dados recuperados a partir da Internet. Este problema motivou o desenvolvimento deste trabalho. Mesmo com o auxílio de várias ferramentas de pesquisa na Internet, buscando realizar pesquisas sobre assuntos específicos, o usuário ainda tem que manipular em seu computador pessoal uma grande quantidade de informação, pois estas ferramentas não realizam um processo de seleção detalhado. Ou seja, são recuperados muitos dados não interessantes ao usuário. Existe, também, uma grande diversidade de assuntos e padrões de transferência e armazenamento da informação criando os mais heterogêneos ambientes de pesquisa e consulta de dados. Esta heterogeneidade faz com que o usuário da rede deva conhecer todo um conjunto de padrões e ferramentas a fim de obter a informação desejada. No entanto, a maior dificuldade de manipulação esta ligada aos formatos de armazenamento não estruturados ou pouco estruturados, como, por exemplo: arquivos textos, Mails (correspondência eletrônica) e artigos de News (jornais eletrônicos). Nestes formatos, o entendimento do documento exige a leitura do mesmo pelo usuário, o que muitas vezes acarreta em um gasto de tempo desnecessário, pois o documento, por exemplo, pode não ser de interesse deste ou, então, ser de interesse, mas sua leitura completa só seria útil posteriormente. Várias informações, como chamadas de trabalhos para congressos, preços de produtos e estatísticas econômicas, entre outras, apresentam validade temporal. Outras informações são atualizadas periodicamente. Muitas dessas características temporais são explicitas, outras estão implícitas no meio de outros tipos de dados. Isto torna muito difícil a recuperação de tal tipo de informação, gerando, várias vezes, a utilização de informações desatualizadas, ou a perda de oportunidades. Desta forma, o grande volume de dados em arquivos pessoais obtidos a partir da Internet criou uma complexa tarefa de gerenciamento dos mesmos em conseqüência da natureza não estruturada dos documentos recuperados e da complexidade da análise do tempo de validade inerente a estes dados. Com o objetivo de satisfazer as necessidades de seleção e conseqüente manipulação das informações existentes a nível local (computador pessoal), neste trabalho, é descrito um sistema para extração e sumarização destes dados, utilizando conceitos de IE (Information Extraction) e Sistemas Baseados em Conhecimento. Os dados processados são parcialmente estruturados ou não estruturados, sendo manipulados por um extrator configurado a partir de bases de conhecimento geradas pelo usuário do sistema. O objetivo final desta dissertação é a implementação do Sistema de Extração Semântica de Informações, o qual permite a classificação dos dados extraídos em classes significativas para o usuário e a determinação da validade temporal destes dados a partir da geração de uma base de dados estruturada. / One of the most challenging area in Computer Science is related to Internet technology. This network offers to the users a large variety and amount of information, mainly, data storage in unstructured or semi-structured formats. However, the vast data volume and heterogeneity transforms the retrieved data manipulation a very arduous work. This problem was the prime motivation of this work. As with many tools for data retrieval and specific searching, the user has to manipulate in his personal computer an increasing amount of information, because these tools do not realize a precise data selection process. Many retrieval data are not interesting for the user. There are, also, a big diversity of subjects and standards in information transmission and storage, creating the most heterogeneous environments in data searching and retrieval. Due to this heterogeneity, the user has to know many data standards and searching tools to obtain the requested information. However, the fundamental problem for data manipulation is the partially or fully unstructured data formats, as text, mail and news data structures. For files in these formats, the user has to read each of the files to filter the relevant information, originating a loss of time, because the document could be not interesting for the user, or if it is interesting, its complete reading may be unnecessary at the moment. Some information as call-for-papers, product prices, economic statistics and others, has associated a temporal validity. Other information are updated periodically. Some of these temporal characteristics are explicit, others are implicitly embedded in other data types. As it is very difficult to retrieve the temporal data automatically, which generate, many times, the use of invalid information, as a result, some opportunities are lost. On this paper a system for extraction and summarizing of data is described. The main objective is to satisfy the user's selection needs and consequently information manipulation stored in a personal computer. To achieve this goal we are employed the concepts of Information Extraction (IE) and Knowledge Based Systems. The input data manipulation is done by an extraction procedure configured by a user who defined knowledge base. The objective of this paper is to develop a System of Semantic Extraction of Information which classifies the data extracted in meaningful classes for the user and to deduce the temporal validity of this data. This goal was achieved by the generation of a structured temporal data base.

The main aim of the thesis Strategic management of a Production Co-operative is to provide a detailed analysis of the external and internal environment of the Kovona Production Co-operative based in Brno, and the strategic measures, which result from the mentioned analyses. The theoretical part indicates the general methods of strategic analysis with the employment of the chosen methods. In the practical part, the chosen methods were applied on the situation of the production co-operative. Based on the analysis of the external environment, opportunities and threats, which are beneficial or endangering for running the production co-operative which employs handicapped people, are identified. The result of the analysis of the internal environment is the identification of strengths and weaknesses of the production co-operative. The factors of the external and internal environment are evaluated by means of EFE and IFE matrixes. The next part uses chosen tools for the strategy determination: Internal-external matrix and SWOT matrix. Based on the achieved results, there were proposed several strategic alternatives. These strategies should lead to strengthening of the current position of the production co-operative on the market, improvement in its competitiveness by means of more intensive use of promotional tools, implementation of the reorganization of production and the expansion of distribution channels.