1,721,026 research outputs found
Storm Surges Congress 2010
No full textStorm surges represent a major type of natural hazard, frequently causing substantial losses of lives and economic damages.
Besides climate change drivers, storm surges are exacerbated by anthropogenic forcing including intensive land and sea use along the river-coast continuum.
How do we deal with the present level of risk?
How do we respond to changing future conditions?
Answers require interdisciplinary approaches and to overcome the traditional fragmentation in scientific and coastal user discussions and management systems. We strongly encourage multiple stakeholders, coastal users and decision-makeres, scientists, and particularly young colleagues from diverse fields of expertise, to participate with knowledge and share their experience.
Plenary sessions and moderated poster sessions underpinned by round table discussions should encourage cross-disciplinary exchange. The goal is also to provide useful outcome information subsequent to the congress in various forms of dissemination.
Please feel encouraged to forward this information to other interessted parties
UNITOR-CORE TYPED: Combining Text Similarity and Semantic Filters through SV Regression
No full textThis paper presents the UNITOR system that participated in the ∗SEM 2013 shared task on Semantic Textual Similarity (STS). The task is modeled as a Support Vector (SV) regression problem, where a similarity scoring function between text pairs is acquired from examples. The proposed approach has been implemented in a system that aims at providing high applicability and robustness, in order to reduce the risk of over-fitting over a specific datasets. Moreover, the approach does not require any manually coded resource (e.g. WordNet), but mainly exploits distributional analysis of unlabeled corpora. A good level of accuracy is achieved over the shared task: in the Typed STS task the proposed system ranks in 1st and 2nd position
UNITOR: Combining semantic text similarity functions through SV Regression
No full textThis paper presents the UNITOR system that participated to the SemEval 2012 Task 6: Semantic Textual Similarity (STS). The task is here modeled as a Support Vector (SV) regression problem, where a similarity scoring function between text pairs is acquired from examples. The semantic relatedness between sentences is modeled in an unsupervised fashion through different similarity functions, each capturing a specific semantic aspect of the STS, e.g. syntactic vs. lexical or topical vs. paradigmatic similarity. The SV regressor effectively combines the different models, learning a scoring function that weights individual scores in a unique resulting STS. It provides a highly portable method as it does not depend on any manually built resource (e.g. WordNet) nor controlled, e.g. aligned, corpus
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
Space projections as distributional models for semantic composition
Full text linkEmpirical distributional methods account for the meaning of syntactic structures by combining word vectors according to algebraic operators. In this paper, a novel approach for semantic composition based on space projection techniques over lexical vector representations is proposed. In line with the principle of compositionality, the meaning of a phrase is modeled in terms of the subset of properties shared by co-occurring words. Syntactic bi-grams are thus projected in the so called Support Subspace, corresponding to such properties. State-of-the-art results are achieved in a well known phrase similarity task, used as a benchmark for this class of methods. © 2012 Springer-Verlag
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
Algebraic compositional models for semantic similarity in ranking and clustering
No full textAlthough distributional models of word meaning have been widely used in Information Retrieval achieving an effective representation and generalization schema of words in isolation, the composition of words in phrases or sentences is still a challenging task. Different methods have been proposed to account on syntactic structures to combine words in term of algebraic operators (e.g. tensor product) among vectors that represent lexical constituents. In this paper, a novel approach for semantic composition based on space projection techniques over the basic geometric lexical representations is proposed. In the geometric perspective here pursued, syntactic bi-grams are projected in the so called Support Subspace, aimed at emphasizing the semantic features shared by the compound words and better capturing phrase-specific aspects of the involved lexical meanings. State-of-the-art results are achieved in a well known benchmark for phrase similarity task and the generalization capability of the proposed operators is investigated in a cross-linguistic scenario, i.e. in the English and Italian Language
Insearch: A platform for enterprise semantic search
No full textThis paper discusses the system targeted in the INSEARCH EU project. It embodies most of the state-of-the-art techniques for Enterprise Semantic Search: highly accurate lexical semantics, semantic web tools, collaborative knowledge management and personalization. An advanced information retrieval system has been developed integrating robust semantic technologies and industry-standard software architectures for proactive search as well as personalized domain-specific classification and ranking functionalities
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