937 resultados para text analysis


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Experiences showed that developing business applications that base on text analysis normally requires a lot of time and expertise in the field of computer linguistics. Several approaches of integrating text analysis systems with business applications have been proposed, but so far there has been no coordinated approach which would enable building scalable and flexible applications of text analysis in enterprise scenarios. In this paper, a service-oriented architecture for text processing applications in the business domain is introduced. It comprises various groups of processing components and knowledge resources. The architecture, created as a result of our experiences with building natural language processing applications in business scenarios, allows for the reuse of text analysis and other components, and facilitates the development of business applications. We verify our approach by showing how the proposed architecture can be applied to create a text analytics enabled business application that addresses a concrete business scenario. © 2010 IEEE.

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Concept inventory tests are one method to evaluate conceptual understanding and identify possible misconceptions. The multiple-choice question format, offering a choice between a correct selection and common misconceptions, can provide an assessment of students' conceptual understanding in various dimensions. Misconceptions of some engineering concepts exist due to a lack of mental frameworks, or schemas, for these types of concepts or conceptual areas. This study incorporated an open textual response component in a multiple-choice concept inventory test to capture written explanations of students' selections. The study's goal was to identify, through text analysis of student responses, the types and categorizations of concepts in these explanations that had not been uncovered by the distractor selections. The analysis of the textual explanations of a subset of the discrete-time signals and systems concept inventory questions revealed that students have difficulty conceptually explaining several dimensions of signal processing. This contributed to their inability to provide a clear explanation of the underlying concepts, such as mathematical concepts. The methods used in this study evaluate students' understanding of signals and systems concepts through their ability to express understanding in written text. This may present a bias for students with strong written communication skills. This study presents a framework for extracting and identifying the types of concepts students use to express their reasoning when answering conceptual questions.

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Despite the central role of the media in contemporary society, studies examining the rhetorical practices of journalists are rare in organization and management research. We know little of the textual micro strategies and techniques through which journalists convey specific messages to their readers. Partially to fill the gap, this paper outlines a methodological framework that combines three perspectives of text analysis and interpretation: critical discourse analysis, systemic functional grammar and rhetorical structure theory. Using this framework, we engage in a close reading of a single media text (a press article) on a recent case of industrial restructuring in the financial services. In our empirical analysis, we focus on key arguments put forward by the journalists’ rhetorical constructions. We maintain that these arguments—which are not frame-breaking but rather tend to confirm existing presuppositions held by the audience—are an essential part of the legitimization and naturalization of specific management ideas and ideologies.

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This class introduces basics of web mining and information retrieval including, for example, an introduction to the Vector Space Model and Text Mining. Guest Lecturer: Dr. Michael Granitzer Optional: Modeling the Internet and the Web: Probabilistic Methods and Algorithms, Pierre Baldi, Paolo Frasconi, Padhraic Smyth, Wiley, 2003 (Chapter 4, Text Analysis)

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Complex networks have been increasingly used in text analysis, including in connection with natural language processing tools, as important text features appear to be captured by the topology and dynamics of the networks. Following previous works that apply complex networks concepts to text quality measurement, summary evaluation, and author characterization, we now focus on machine translation (MT). In this paper we assess the possible representation of texts as complex networks to evaluate cross-linguistic issues inherent in manual and machine translation. We show that different quality translations generated by NIT tools can be distinguished from their manual counterparts by means of metrics such as in-(ID) and out-degrees (OD), clustering coefficient (CC), and shortest paths (SP). For instance, we demonstrate that the average OD in networks of automatic translations consistently exceeds the values obtained for manual ones, and that the CC values of source texts are not preserved for manual translations, but are for good automatic translations. This probably reflects the text rearrangements humans perform during manual translation. We envisage that such findings could lead to better NIT tools and automatic evaluation metrics.

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Many countries recognized the potential of medicaltourism as an alternative source of economic growth. Especially after theeconomic crisis many Asian countries joined medical tourism in hopes to escapethe severe financial difficulty. However, yet only few countries have managedto become a famous medical tourism destination. With growing number ofcompetitors, newly joined countries of medical tourism, face the difficulty inintroducing them self as attractive medical tourism destination. South Koreaas a new medical tourism destination, should consider what to offer to themedical tourists to attract them. The aim of the thesis was to investigate aspects influencing the participationof medical tourists to discover how South Korea could develop anattractive medical tourism destination. After examining the casestudy and results from the text analysis, researcher reached to the conclusionthat quality, cost and accessibility to treatment are the major reasons toparticipate in medical tourism. Also in the fierce competition, it is importantto develop differentiated offers from other destinations. Therefore, Koreashould concentrate on specialized treatments and ICT system to become anattractive medical tourism destination.

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The paper presents an approach to extraction of facts from texts of documents. This approach is based on using knowledge about the subject domain, specialized dictionary and the schemes of facts that describe fact structures taking into consideration both semantic and syntactic compatibility of elements of facts. Actually extracted facts combine into one structure the dictionary lexical objects found in the text and match them against concepts of subject domain ontology.

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The principal feature of ontology, which is developed for a text processing, is wider knowledge representation of an external world due to introduction of three-level hierarchy. It allows to improve semantic interpretation of natural language texts.

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With the dramatic growth of text information, there is an increasing need for powerful text mining systems that can automatically discover useful knowledge from text. Text is generally associated with all kinds of contextual information. Those contexts can be explicit, such as the time and the location where a blog article is written, and the author(s) of a biomedical publication, or implicit, such as the positive or negative sentiment that an author had when she wrote a product review; there may also be complex context such as the social network of the authors. Many applications require analysis of topic patterns over different contexts. For instance, analysis of search logs in the context of the user can reveal how we can improve the quality of a search engine by optimizing the search results according to particular users; analysis of customer reviews in the context of positive and negative sentiments can help the user summarize public opinions about a product; analysis of blogs or scientific publications in the context of a social network can facilitate discovery of more meaningful topical communities. Since context information significantly affects the choices of topics and language made by authors, in general, it is very important to incorporate it into analyzing and mining text data. In general, modeling the context in text, discovering contextual patterns of language units and topics from text, a general task which we refer to as Contextual Text Mining, has widespread applications in text mining. In this thesis, we provide a novel and systematic study of contextual text mining, which is a new paradigm of text mining treating context information as the ``first-class citizen.'' We formally define the problem of contextual text mining and its basic tasks, and propose a general framework for contextual text mining based on generative modeling of text. This conceptual framework provides general guidance on text mining problems with context information and can be instantiated into many real tasks, including the general problem of contextual topic analysis. We formally present a functional framework for contextual topic analysis, with a general contextual topic model and its various versions, which can effectively solve the text mining problems in a lot of real world applications. We further introduce general components of contextual topic analysis, by adding priors to contextual topic models to incorporate prior knowledge, regularizing contextual topic models with dependency structure of context, and postprocessing contextual patterns to extract refined patterns. The refinements on the general contextual topic model naturally lead to a variety of probabilistic models which incorporate different types of context and various assumptions and constraints. These special versions of the contextual topic model are proved effective in a variety of real applications involving topics and explicit contexts, implicit contexts, and complex contexts. We then introduce a postprocessing procedure for contextual patterns, by generating meaningful labels for multinomial context models. This method provides a general way to interpret text mining results for real users. By applying contextual text mining in the ``context'' of other text information management tasks, including ad hoc text retrieval and web search, we further prove the effectiveness of contextual text mining techniques in a quantitative way with large scale datasets. The framework of contextual text mining not only unifies many explorations of text analysis with context information, but also opens up many new possibilities for future research directions in text mining.

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Historically, asset management focused primarily on the reliability and maintainability of assets; organisations have since then accepted the notion that a much larger array of processes govern the life and use of an asset. With this, asset management’s new paradigm seeks a holistic, multi-disciplinary approach to the management of physical assets. A growing number of organisations now seek to develop integrated asset management frameworks and bodies of knowledge. This research seeks to complement existing outputs of the mentioned organisations through the development of an asset management ontology. Ontologies define a common vocabulary for both researchers and practitioners who need to share information in a chosen domain. A by-product of ontology development is the realisation of a process architecture, of which there is also no evidence in published literature. To develop the ontology and subsequent asset management process architecture, a standard knowledge-engineering methodology is followed. This involves text analysis, definition and classification of terms and visualisation through an appropriate tool (in this case, the Protégé application was used). The result of this research is the first attempt at developing an asset management ontology and process architecture.

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Short-termism among firms, the tendency to excessively discount long-term benefits and favour less valuable short-term benefits, has been a prominent issue in business and public policy debates but research to date has been inconclusive. We study how managers frame, interpret, and resolve problems of intertemporal choice in actual decisions by using computer aided text analysis to measure the frequency of top-team temporal references in 1653 listed Australian firms between 1992-2005. Contrary to short-termism arguments we find evidence of a significant general increase in Future orientation and a significant decrease in Current/Past orientation. We also show top-teams’ temporal orientation is related to their strategic orientation, specifically the extent to which they focus on Innovation-Expansion and Capacity Building.

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Manufacturing managers have a measurable mindset (or frame) that structures their response to the manufacturing environment. Most importantly, this frame represents a set of assumptions about the relative prominence of concepts in the manufacturing domains, about the nature of people, and about the sensemaking processes required to understand the nature of the manufacturing environment as seen through the eyes of manufacturing managers. This paper uses work in the area of text analysis and extends the scope of a methodology that has been approached from two different directions by Carley ( Journal of Organizational Behavior , 18 (51), 533-558, 1997) and Gephart ( Journal of Organizational Behavior , 18 (51), 583-622, 1997). This methodology is termed collocate analysis. Based on the analysis of transcripts of interviews of Australian manufacturing managers mind maps of the concepts used by these managers have been constructed. From an analysis of these mind maps it is argued that strategy plays a minor role in their thinking second only to the improvement domain, whereas design and related concepts play a dominant role in their day-to-day thinking.

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Brisbane is provincial city that has been developing rapidly since the early 1990s. The growth and development of its public and semi-public spaces means there are many more ways to engage with the city than was previously possible. --------- I suggest the city’s new and transformed spaces have enabled 2 important developments 1) a growth in forms of sociability and encounters with difference and 2) the negotiation of civic competencies. --------- The paper draws upon research conducted during a PhD project which used multi-method approaches - including qualitative [interviews] and quantitative data [surveys], psychoanalytic theory and text analysis.The study also made connections between the real city and the discursive city to argue that urban experience is constituted both materially and imaginatively.

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A review of theoretical principals and practice of school-based approaches to critical literacy, with a specific focus on the middle years of schooling.

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Environmental education is a field which has only come of age since the late nineteen sixties. While its content and practice have been widely debated and researched, its leadership has been minimally studied and, therefore, is only partially understood. The role of mentoring in the development of leaders has been alluded to, but has attracted scant research. Therefore, this study explores the importance of mentoring during the personal and professional development of leaders in environmental education. Four major research questions were investigated. Firstly, have leaders been men to red during their involvement with environmental education? Secondly, when and how has that mentoring taken place? Thirdly, what was the personal and professional effectiveness of the mentoring relationship? Fourthly, is there any continuation of the mentoring process which might be appropriate for professional development within the field of environmental education? Leaders were solicited from a broad field of environmental educators including teachers, administrators, academics, natural resource personnel, business and community persons. They had to be recognized as active leaders across several environmental education networks. The research elicited qualitative and quantitative survey data from fifty seven persons in Queensland, Australia and Colorado, USA. Seventeen semi-structured interviews were subsequently conducted with selected leaders who had nominated their mentors. This led to a further thirteen 'linked interviews' with some of the mentors' mentors and new mentorees. The interview data is presented as four cases reflecting pairs, triads, chains and webs of relationships- a major finding of the research process. The analysis of the data from the interviews and the surveys was conducted according to a grounded theory approach and was facilitated by NUD.IST, a computer program for non-numerical text analysis. The findings of the study revealed many variations on the classical mentoring patterns found in the literature. Gender and age were not seen as mportant factors, as there were examples of contemporaries in age, older men to younger women, older women to younger men, and women to women. Personal compatibility, professional respect and philosophical congruence were critical. Mentoring was initiated from early, mid and late career stages with the average length of the relationship being fourteen years. There was seldom an example of the mentoree using the mentor for hierarchical career climbing, although frequent career changes were made. However, leadership actions were found to increase after the intervention of a mentoring relationship. Three major categories of informal mentoring were revealed - perceived,acknowledged and deliberate. Further analysis led to the evolution of the core concept, a 'cascade of influence'. The major finding of this study was that this sample of leaders, mentors and new mentorees moved from the perception of having been mentored to the acknowledgment of these relationships and an affirmation of their efficacy for both personal and professional growth. Hence, the participants were more likely to continue future mentoring, not as a serendipitous happening, but through a deliberate choice. Heightened awareness and more frequent 'cascading' of mentoring have positive implications for the professional development of future leaders in environmental education in both formal and informal settings. Effective mentoring in environmental education does not seek to create 'clones' of the mentors, but rather to foster the development of autonomous mentorees who share a philosophical grounding. It is a deliberate invitation to 'join the clan'.