188,421 research outputs found

    Deep Adaptive Learning for Writer Identification based on Single Handwritten Word Images

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    There are two types of information in each handwritten word image: explicit information which can be easily read or derived directly, such as lexical content or word length, and implicit attributes such as the author's identity. Whether features learned by a neural network for one task can be used for another task remains an open question. In this paper, we present a deep adaptive learning method for writer identification based on single-word images using multi-task learning. An auxiliary task is added to the training process to enforce the emergence of reusable features. Our proposed method transfers the benefits of the learned features of a convolutional neural network from an auxiliary task such as explicit content recognition to the main task of writer identification in a single procedure. Specifically, we propose a new adaptive convolutional layer to exploit the learned deep features. A multi-task neural network with one or several adaptive convolutional layers is trained end-to-end, to exploit robust generic features for a specific main task, i.e., writer identification. Three auxiliary tasks, corresponding to three explicit attributes of handwritten word images (lexical content, word length and character attributes), are evaluated. Experimental results on two benchmark datasets show that the proposed deep adaptive learning method can improve the performance of writer identification based on single-word images, compared to non-adaptive and simple linear-adaptive approaches.Comment: Under view of Pattern Recognitio

    Integrating modes of policy analysis and strategic management practice : requisite elements and dilemmas

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    There is a need to bring methods to bear on public problems that are inclusive, analytic, and quick. This paper describes the efforts of three pairs of academics working from three different though complementary theoretical foundations and intervention backgrounds (i.e., ways of working) who set out together to meet this challenge. Each of the three pairs had conducted dozens of interventions that had been regarded as successful or very successful by the client groups in dealing with complex policy and strategic problems. One approach focused on leadership issues and stakeholders, another on negotiating competitive strategic intent with attention to stakeholder responses, and the third on analysis of feedback ramifications in developing policies. This paper describes the 10 year longitudinal research project designed to address the above challenge. The important outcomes are reported: the requisite elements of a general integrated approach and the enduring puzzles and tensions that arose from seeking to design a wide-ranging multi-method approach

    How can heat maps of indexing vocabularies be utilized for information seeking purposes?

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    The ability to browse an information space in a structured way by exploiting similarities and dissimilarities between information objects is crucial for knowledge discovery. Knowledge maps use visualizations to gain insights into the structure of large-scale information spaces, but are still far away from being applicable for searching. The paper proposes a use case for enhancing search term recommendations by heat map visualizations of co-word relation-ships taken from indexing vocabulary. By contrasting areas of different "heat" the user is enabled to indicate mainstream areas of the field in question more easily.Comment: URL workshop proceedings: http://ceur-ws.org/Vol-1311

    Bibliometric cartography of information retrieval research by using co-word analysis

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    The aim of this study is to map the intellectual structure of the field of Information Retrieval (IR) during the period of 1987-1997. Co-word analysis was employed to reveal patterns and trends in the IR field by measuring the association strengths of terms representative of relevant publications or other texts produced in IR field. Data were collected from Science Citation Index (SCI) and Social Science Citation Index (SSCI) for the period of 1987-1997. In addition to the keywords added by the SCI and SSCI databases, other important keywords were extracted from titles and abstracts manually. These keywords were further standardized using vocabulary control tools. In order to trace the dynamic changes of the IR field, the whole 11-year period was further separated into two consecutive periods: 1987-1991 and 1992-1997. The results show that the IR field has some established research themes and it also changes rapidly to embrace new themes

    WAYLA - Generating Images from Eye Movements

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    We present a method for reconstructing images viewed by observers based only on their eye movements. By exploring the relationships between gaze patterns and image stimuli, the "What Are You Looking At?" (WAYLA) system learns to synthesize photo-realistic images that are similar to the original pictures being viewed. The WAYLA approach is based on the Conditional Generative Adversarial Network (Conditional GAN) image-to-image translation technique of Isola et al. We consider two specific applications - the first, of reconstructing newspaper images from gaze heat maps, and the second, of detailed reconstruction of images containing only text. The newspaper image reconstruction process is divided into two image-to-image translation operations, the first mapping gaze heat maps into image segmentations, and the second mapping the generated segmentation into a newspaper image. We validate the performance of our approach using various evaluation metrics, along with human visual inspection. All results confirm the ability of our network to perform image generation tasks using eye tracking data

    Exploratory topic modeling with distributional semantics

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    As we continue to collect and store textual data in a multitude of domains, we are regularly confronted with material whose largely unknown thematic structure we want to uncover. With unsupervised, exploratory analysis, no prior knowledge about the content is required and highly open-ended tasks can be supported. In the past few years, probabilistic topic modeling has emerged as a popular approach to this problem. Nevertheless, the representation of the latent topics as aggregations of semi-coherent terms limits their interpretability and level of detail. This paper presents an alternative approach to topic modeling that maps topics as a network for exploration, based on distributional semantics using learned word vectors. From the granular level of terms and their semantic similarity relations global topic structures emerge as clustered regions and gradients of concepts. Moreover, the paper discusses the visual interactive representation of the topic map, which plays an important role in supporting its exploration.Comment: Conference: The Fourteenth International Symposium on Intelligent Data Analysis (IDA 2015

    Уклонение от уплаты налогов: библиометрический анализ точек зрения власти, бизнеса и науки

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    Статья посвящена анализу публикаций, касающихся проблемы уклонения от уплаты налогов. Эта тема привлекает пристальное внимание не только научного сообщества. В статье исследуется соответствие проблематики научных работ по уклонению от уплаты налогов практическим вопросам, обсуждаемым заинтересованными лицами. В качестве источника научных публикаций по данной тематике использовалась электронная база e-Library. В круг заинтересованных лиц, напрямую зависящих от правил налогообложения, входят бизнессообщество и государственные органы. Для них источниками информации по исследуемой теме являются электронная база публикаций издательского дома «Коммерсантъ» и «Российская газета». Для анализа отобрана 301 публикация за 2013-2015 гг. Изучение соответствия проблематики проводилось путем сравнения публикационной активности в разрезе видов публикаций. На первом этапе исследования был выполнен качественный контент-анализ посредством выявления общих тем, обсуждаемых в публикациях. Затем проводился количественный анализ через сравнение распределения публикаций по конкретной теме из каждого источника. Для количественного анализа и визуализации результатов использовались методы библиометрического анализа и картирования. Расчеты производились с помощью программного продукта QDA Miner v.5.0 модуль WordStat v.7.1.7. В результате исследования были сделаны выводы, что самыми популярными темами, интерес к которым не меняется, являются: изменение законодательства, законотворчество и усиление принуждения. Темы, к которым за рассматриваемый период снизился интерес, касаются международных аспектов налогообложения, теневой деятельности, собственности и инвестиций. Отмечено выраженное возрастание интереса сообщества к фирмам-однодневкам, руководству компаний, а также к вопросам штрафов и пени. Исследование позволило выявить определенное несоответствие тем, обсуждаемых бизнесом и властью, по сравнению с темами научных публикаций. Распространенные в научных публикациях темы (теневая экономика, коррупция, фирмы-однодневки, взносы на социальное страхование), гораздо реже встречаются на ресурсах издательского дома «Коммерсантъ» и в «Российской газете», сосредотачивающих основное внимание на вопросах законотворчества и обсуждения изменений в законодательстве. Анализ взаимосвязей в текстах в соответствии с источниками и годом публикации показал, что темы научных исследований сближаются с проблемами, рассматриваемыми властью, а бизнес-сообщество в большей степени вовлекается обсуждение правовой проблематики, т. е. точка зрения власти во многом определяет обсуждение темы уклонения от налогов бизнес-сообществом, и научными кругами. Таким образом, библиометрические методы анализа текстов могут применяться для проведения научных исследований, составления обзоров литературы и тематического поиска информации.This article analyzes the publications relating to the problem of tax evasion. This topic is attractive not only for the academic community, but also for public at whole. The article explores to what extent the scientific publications on tax evasion correspond to practical issues discussed among the stakeholders. We used the electronic database of e-Library as a source of scientific publications on the subject. The principal stakeholders directly dependent on the taxation are the taxpayers and public authorities. We used the electronic database of publications «Kommersant» publishing house and the «Rossiyskaya Gazeta» to reflect issues discussed among the stakeholders. We selected for analyze 301 publications for the period of 2013-2015. The study was conducted by comparing the publication activity by types and period of publications. In the first stage of the study we have done the qualitative content analysis by identification the common themes discussed in hole sample of publications. Then, a quantitative analysis was conducted by comparing the distribution of publications on a particular topic from each source. We used bibliometric analysis method for the quantitative and bibliographic mapping method to visualize the results of research. Calculations were performed using the software QDA Miner v.5.0 module WordStat v.7.1.7. As a result, studies have concluded that the most popular topics of interest for which no changes are: changes in legislation, legislation and increased enforcement. Using the results of the conducted study, we can identify the main similarities and differences between the monitored sources. We can see the special attention to the: Legislation changes, Law enforcement, Entrepreneurship. Marked reduction of interest can be noted regarding to the following topics: International aspects of taxation, Shadow economy, Ownership, property, investment. The growth of interest can be noted in relation to the following topics: Directorship, Article of the Tax Code, Short-lived companies, Arrears and fines. The study revealed a certain disparity between the topics discussed among academic community and stakeholders. The topics discussed in the majority of scientific texts (shadow economy, corruption, the firm one-day, social security contributions), a much rarer can be found in the publication of «Kommersant» and «Rossiyskaya Gazeta» which focuses mainly on matters of legislation. Analysis of the relationships in the texts according to the source and year of publication showed that research topics converge with issues considered by the public authorities. The business community more involved in discussion the legal issues, because the government notion works upon the impression about tax evasion of the business community and academia. Thus, bibliometric text analysis techniques can be used for research, preparation of literature reviews and thematic information retrieval
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