1,721,014 research outputs found

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    A PROPOSAL OF FUZZY MULTIDIMENSIONAL ASSOCIATION RULES

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    Association rules that involve two or more dimensions or predicates can be referred as multidimensional association rules. Rather than searching for frequent itemsets (as is done in mining single-dimensional association rules), in multidimensional association rules, we search for frequent predicate sets. In general, there are two types of multidimensional association rules, namely interdimension association rules and hybrid-dimension association rules. Interdimension association rules are multidimensional association rules with no repeated predicates. This paper introduces a method for generating interdimension association rules. A more meaningful association rules can be provided by generalizing crisp value of attributes to be fuzzy value. To generate the multidimensional association rules implying fuzzy value, this paper introduces an alternative method for mining the rules by searching for the predicate sets

    PENGGUNAAN HIBRIDISASI GENETICS ALGORITHMS DAN FUZZY SETS UNTUK MEMPRODUKSI PAKET SOAL

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    At least, two important factors, discrimination and difficulty, should be considered in determing whether a problem should be in a packet of problems produced for students entrance examination at a university. The higher the discrimination degree of a problem, the better the problem is used to make a selection of participants based on their intellectual capability. How to provide a packet of entrance examination problems satisfying a determined pattern of discrimination and difficulty is a major problem in this paper for which an algorithm, it can be proved that the beneficiary of applying fuzzy sets and fuzzy relation in determing the first chromosome in the process of GA is that the process can reach tolerable solutions faster. Maximum number of generation is still needed as a threshold to overcome the problem of run time system overflow. Generally, the problems in the form of passages tend to have lower fitnest cost. Abstract in Bahasa Indonesia : Proses penyusunan paket soal (misalnya soal untuk test seleksi masuk universitas) yang diambil dari suatu bank soal, minimal harus memperhatikan dua aspek penting yaitu: tingkat kesulitan dan tingkat diskriminan soal. Semakin tinggi tingkat diskriminan suatu soal, semakin baik soal tersebut dipakai untuk menyeleksi kemampuan peserta test. Permasalahan yang dihadapi adalah bagaimana agar pembuat soal dapat memilih dan menentukan kombinasi soal-soal yang tepat (optimum) sehingga dapat memenuhi tingkat kesulitan dan diskriminan yang dikehendaki. Untuk menyelesaikan masalah ini, diperkenalkan suatu algoritma yang disusun dengan menggunakan hibridisasi metode Genetics Algorithm dan fuzzy sets. Dari hasil pengujian, didapatkan bahwa penggunaan fuzzy sets dan fuzzy relations dalam pemilihan kromoson awal akan lebih mempercepat pencapaian tolerable solutions. Tetap dibutuhkan treshould maksimum jumlah generasi yang dilakukan untuk mencegah run time sistem overflow. Soal bacaan cenderung memiliki nilai Fitnest Cost yang lebih rendah daripada nilai Fitnest Cost untuk paket soal bukan soal bacaan. Kata kunci: genetics algorithm, fuzzy sets, hibridization method

    Study on Rough Sets and Fuzzy Sets in Constructing Intelligent Information System

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    Since human being is not an omniscient and omnipotent being, we are actually living in an uncertain world. Uncertainty was involved and connected to every aspect of human life as a quotation from Albert Einstein said: �As far as the laws of mathematics refer to reality, they are not certain. And as far as they are certain, they do not refer to reality.� The most fundamental aspect of this connection is obviously shown in human communication. Naturally, human communication is built on the perception1-based information instead of measurement-based information in which perceptions play a central role in human cognition [Zadeh, 2000]. For example, it is naturally said in our communication that �My house is far from here.� rather than let say �My house is 12,355 m from here�. Perception-based information is a generalization of measurement-based information, where perception-based information such as �John is excellent.� is hard to represent by measurement-based version. Perceptions express human subjective view. Consequently, they tend to lead up to misunderstanding. Measurements then are needed such as defining units of length, time, etc., to provide objectivity as a means to overcome misunderstanding. Many measurers were invented along with their methods and theories of measurement. Hence, human cannot communicate with measurers including computer as a product of measurement era unless he uses measurement-based information. Perceptions are intrinsic aspect in uncertainty-based information. In this case, information may be incomplete, imprecise, fragmentary, not fully reliable, vague, contradictory, or deficient in some other way. 1In psychology, perception is understood as a process of translating sensory stimulation into an organized experience Generally, these various information deficiencies may express different types of uncertainty. It is necessary to construct a computer-based information system called intelligent information system that can process uncertainty-based information. In the future, computers are expected to be able to make communication with human in the level of perception. Many theories were proposed to express and process the types of uncertainty such as probability, possibility, fuzzy sets, rough sets, chaos theory and so on. This book extends and generalizes existing theory of rough set, fuzzy sets and granular computing for the purpose of constructing intelligent information system. The structure of this book is the following: In Chapter 2, types of uncertainty in the relation to fuzziness, probability and evidence theory (belief and plausibility measures) are briefly discussed. Rough set regarded as another generalization of crisp set is considered to represent rough event in the connection to the probability theory. Special attention will be given to formulation of fuzzy conditional probability relation generated by property of conditional probability of fuzzy event. Fuzzy conditional probability relation then is used to represent similarity degree of two fuzzy labels. Generalization of rough set induced by fuzzy conditional probability relation in terms of covering of the universe is given in Chapter 3. In the relation to fuzzy conditional probability relation, it is necessary to consider an interesting mathematical relation called weak fuzzy similarity relation as a generalization of fuzzy similarity relation proposed by Zadeh [1995]. Fuzzy rough set and generalized fuzzy rough set are proposed along with the generalization of rough membership function. Their properties are examined. Some applications of these methods in information system such as α-redundancy of object and dependency of domain attributes are discussed. In addition, multi rough sets based on multi-context of attributes in the presence of multi-contexts information system is defined and proposed in Chapter 4. In the real application, depending on the context, a given object may have different values of attributes. In other words, set of attributes might be represented based on different context, where they may provide different values for a given object. Context can be viewed as background or situation in which somehow it is necessary to group some attributes as a subset of attributes and consider the subset as a context. Finally, Chapter 5 summarizes all discussed in this book and puts forward some future topics of research

    APPLICATION OF CONDITIONAL PROBABILITY IN PREDICTING INTERVAL PROBABILITY OF DATA QUERYING

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    This paper discusses fuzzification of crisp domain into fuzzy classes providing fuzzy domain. Relationship between two fuzzy domains, Xi and Xj, can be represented by using a matrix, wij. If Xi has n elements of fuzzy data and Xj has m elements of fuzzy data then wij is n x m matrix. Our primary goal in this paper is to generate some formulas for predicting interval probability in the relation to data querying, i.e., given John is 30 years old and he has MS degree, how about his probability to get high salary

    AN ALGORITHM FOR GENERATING SINGLE DIMENSIONAL FUZZY ASSOCIATION RULE MINING

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    Association rule mining searches for interesting relationship among items in a large data set. Market basket analysis, a typical example of association rule mining, analyzes buying habit of customers by finding association between the different items that customers put in their shopping cart (basket). Apriori algorithm is an influential algorithm for mining frequent itemset for generating association rules. For some reasons, Apriori algorithm is not based on human intuitive. To provide a more human-based concept, this paper proposes an alternative algorithm for generating the association rule by utilizing fuzzy sets in the market basket analysis
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