1,721,024 research outputs found
A Relational Unsupervised Approach to Author Identification
No full textIn the last decades speaking and writing habits have changed.
Many works faced the author identification task by exploiting frequencybased
approaches, numeric techniques or writing style analysis. Following
the last approach we propose a technique for author identification
based on First-Order Logic. Specifically, we translate the complex data
represented by natural language text to complex (relational) patterns
that represent the writing style of an author. Then, we model an author
as the result of clustering the relational descriptions associated to the
sentences. The underlying idea is that such a model can express the typical
way in which an author composes the sentences in his writings. So,
if we can map such writing habits from the unknown-author model to
the known-author model, we can conclude that the author is the same.
Preliminary results are promising and the approach seems viable in real
contexts since it does not need a training phase and performs well also
with short texts
Learning and Exploiting Concept Networks with ConNeKTion
No full textStudying, understanding and exploiting the content of a document
collection require automatic techniques that can effectively support
the users in extracting useful information from it and reason with
this information. Concept networks (e.g., taxonomies) may play a
relevant role in this perspective, but are seldom available, and
cannot be manually built and maintained cheaply and reliably. On
the other hand, automated learning of these resources from text
needs to be robust with respect to missing or partial knowledge,
because often only sparse fragments of the target network can be
extracted. This work presents ConNeKTion, a tool that is able to
learn concept networks from plain text and to structure and enrich
them by finding concept generalizations. The proposed
methodologies are general and applicable to any language. It also
provides functionalities for the exploitation of the learned
knowledge, and a control panel that allows the user to comfortably
carry out these activities. Several experiments and applications are
reported, showing the usefulness and flexibility of ConNeKTion
ConNeKTion: A Tool for Exploiting Conceptual Graphs Automatically Learned from Text
No full textStudying, understanding and exploiting the content of a digital library, and extracting useful information thereof, require automatic techniques that can effectively support the users. To this aim, a relevant role can be played by concept taxonomies. Unfortunately, the availability of such a kind of resources is limited, and their manual building and maintenance are costly and error-prone. This work presents ConNeKTion, a tool for conceptual graph learning and exploitation. It allows to learn conceptual graphs from plain text and to enrich them by finding concept generalizations. The resulting graph can be used for several purposes: finding relationships between concepts (if any), filtering the concepts from a particular perspective, keyword extraction and information retrieval. A suitable control panel is provided for the user to comfortably carry out these activities
Emerging targets for the pharmacological tratment of depression: focus on melatonergic system.
No full textAbstract: Depression is a disabling conditìon which adversely affects a person's family, social and work life, and that is associated with
a heavy burden to society Although the available antidepressants have shown their effectiveness and have greatly improved the
prognosis of the disorder,the current management of depression is far from being satisfactory. ln the last years,besides the classical
research involving serotonin, norepineprine and dopamine, non-monoaminergic mechanisms have been explored in the attempt to
discovernew antidepressants. One such innovative approach focused on melatonergic system, as melatonin is involved in synchronizing
circadian rhythms, which are known to be altered ir depression This nanative review aims to provide a comprehensive overview of
different aspects of the melatonergic system, including biochemical and anatomical characteristics, impact on the sleep/wake system, and
implications for the treatment ofdepression. ln particular, the observation that melatonin may promote sleep and synchronize the internal
clock led to development of high-affinity agonists for melatonin receptors (MT) Agomelatine, a naphthalene bioisostere of melatonin,
which combines a potent MTl and MT2 agonism with 5-HT:c receptor antagonism, has been found to be effective in the treatment of
depressive and anxiety symptoms associated with major depression, with rapid and beneficial effects on the regulation of sleep continuity
and quality. If substantiated by further evidence,the observation that melatonergic system dysfunctions contribute to the development of
depression, as well as that the antidepressant action of agomelatine is linked to its binding properties to MT1/MT2 receptors, might open
new avenues for the discovery of antidepressive agents.
Keywords: Agomelatine, antidepressants, arylalkylamine N-acetylhansferase (AANAT), depression, melatonin, melatonin receptors, ramalteon
ConNeKTion: A Tool for Handling Conceptual Graphs Automatically Extracted from Text
No full textStudying, understanding and exploiting the content of a digital library, and extracting useful information thereof, require automatic techniques that can effectively support the users. To this aim, a relevant role can be played by concept taxonomies. Unfortunately, the availability of such a kind of resources is limited, and their manual building and maintenance are costly and error-prone. This work presents ConNeKTion, a tool for conceptual graph learning and exploitation. It allows to learn conceptual graphs from plain text and to enrich them by finding concept generalizations. The resulting graph can be used for several purposes: finding relationships between concepts (if any), filtering the concepts from a particular perspective, extracting keyword, retrieving information and identifying the author. ConNeKTion provides also a suitable control panel, to comfortably carry out these activities
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
A Run Length Smoothing-based Algorithm for Non-Manhattan Document Segmentation
No full textLayout analysis is a fundamental step in automatic document processing, because
its outcome affects all subsequent processing steps. Many different techniques
have been proposed to perform this task. In this work, we propose a general
bottom-up strategy to tackle the layout analysis of (possibly) non-Manhattan
documents, and two specializations of it to handle both bitmap and PS/PDF
sources. A famous approach proposed in the literature for layout analysis was
the RLSA. Here we consider a variant of RLSA, called RLSO (short for “Run-Lengh Smoothing with OR”), that exploits the OR logical operator instead of
the AND and is particularly indicated for the identification of frames in non-Manhattan layouts. Like RLSA, RLSO is based on thresholds, but based on
different criteria than those that work in RLSA. Since setting such thresholds is
a hard and unnatural task for (even expert) users, and no single threshold can fit
all documents, we developed a technique to automatically define such thresholds
for each specific document, based on the distribution of spacing therein. Application
on selected sample documents, that cover a significant landscape of real
cases, revealed that the approach is satisfactory for documents characterized by
the use of a uniform text font size
Variations on the Author
Full text link“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
Full text linkWe 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
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