TagClusters

2010 ◽  
Vol 1 (2) ◽  
pp. 15-28 ◽  
Author(s):  
Ya-Xi Chen ◽  
Rodrigo Santamaría ◽  
Andreas Butz ◽  
Roberto Therón
Keyword(s):  
Semantic Similarity ◽  
Hierarchical Structure ◽  
Online Communities ◽  
Comparative Evaluation ◽  
Semantic Relations ◽  
Spatial Distance ◽  
Font Size ◽  
Alphabetical Order

Many online communities use TagClouds, an aesthetic and easy to understand visualization, to represent popular tags collaboratively generated by their users. However, due to the free nature of tagging, such collaborative tags have linguistic problems and limitations, such as high semantic density. Moreover, the alphabetical order of TagClouds poorly supports a hierarchical exploration among tags. This paper presents an exploration to support semantic understanding of collaborative tags beyond TagClouds. Based on the results of the authors’ survey of practical usages of collaborative tags, they developed a visualization named TagClusters, in which tags are clustered into different groups, with font size representing tag popularity and the spatial distance indicating the semantic similarity between tags. The subgroups in each group and the overlap between groups are highlighted, illustrating the underlying hierarchical structure and semantic relations between groups. The authors conducted a comparative evaluation with TagClouds and TagClusters based on the same tag set. The results confirmed the advantage of TagClusters in facilitating browsing, comparing and comprehending semantic relations between tags.

TagClusters

2012 ◽  
pp. 91-106
Author(s):  
Ya-Xi Chen ◽  
Rodrigo Santamaría ◽  
Andreas Butz ◽  
Roberto Therón
Keyword(s):  
Semantic Similarity ◽  
Hierarchical Structure ◽  
Online Communities ◽  
Comparative Evaluation ◽  
Semantic Relations ◽  
Spatial Distance ◽  
Font Size ◽  
Alphabetical Order

Many online communities use TagClouds, an aesthetic and easy to understand visualization, to represent popular tags collaboratively generated by their users. However, due to the free nature of tagging, such collaborative tags have linguistic problems and limitations, such as high semantic density. Moreover, the alphabetical order of TagClouds poorly supports a hierarchical exploration among tags. This paper presents an exploration to support semantic understanding of collaborative tags beyond TagClouds. Based on the results of the authors’ survey of practical usages of collaborative tags, they developed a visualization named TagClusters, in which tags are clustered into different groups, with font size representing tag popularity and the spatial distance indicating the semantic similarity between tags. The subgroups in each group and the overlap between groups are highlighted, illustrating the underlying hierarchical structure and semantic relations between groups. The authors conducted a comparative evaluation with TagClouds and TagClusters based on the same tag set. The results confirmed the advantage of TagClusters in facilitating browsing, comparing and comprehending semantic relations between tags.

Automatic discovery of word semantic relations using paraphrase alignment and distributional lexical semantics analysis

2010 ◽  
Vol 16 (4) ◽  
pp. 439-467 ◽  
Author(s):  
GAËL DIAS ◽  
RUMEN MORALIYSKI ◽  
JOÃO CORDEIRO ◽  
ANTOINE DOUCET ◽  
HELENA AHONEN-MYKA
Keyword(s):  
Information Extraction ◽  
Semantic Similarity ◽  
Local Environment ◽  
Search Space ◽  
Semantic Space ◽  
Semantic Relations ◽  
Take The Best ◽  
Automatic Discovery ◽  
Semantic Spaces ◽  
Semantic Space Models

AbstractThesauri, which list the most salient semantic relations between words, have mostly been compiled manually. Therefore, the inclusion of an entry depends on the subjective decision of the lexicographer. As a consequence, those resources are usually incomplete. In this paper, we propose an unsupervised methodology to automatically discover pairs of semantically related words by highlighting their local environment and evaluating their semantic similarity in local and global semantic spaces. This proposal differs from all other research presented so far as it tries to take the best of two different methodologies, i.e. semantic space models and information extraction models. In particular, it can be applied to extract close semantic relations, it limits the search space to few, highly probable options and it is unsupervised.

scholarly journals The Internal Structure of Semantic Relations: Effects of Relational Similarity and Typicality

2020 ◽  
Author(s):  
Vencislav Popov ◽  
Margarita Pavlova ◽  
Penka Hristova
Keyword(s):  
Internal Structure ◽  
Semantic Similarity ◽  
Associative Memory ◽  
Learning Task ◽  
Semantic Relations ◽  
Associate Learning ◽  
Relational Similarity ◽  
Analogical Mapping ◽  
Item Level ◽  
Two Factors

We examined whether the processing of semantic relations shows typicality effects similar to those found for the processing of entity concepts. Participants performed four relational processing tasks with the same set of word-pair stimuli: relational exemplar generation; similarity ranking; analogical verification; and a paired-associate learning task. In the similarity ranking task, we gathered separate rankings for relational, role and semantic similarity between word pairs. We found significant correlations at the item level among relational generation frequencies, analogical verification RTs/accuracy and relational luring in associative memory. Relational similarity predicted exemplar generation frequencies, analogical verification RTs/accuracy, and relational luring in associative memory. Role similarity predicted exemplar generation frequency, and analogical verification RTs, but not relational luring. Semantic similarity did not predict any of the tasks, after controlling for the other two factors. Contrary to current theories which posit that semantic similarity is more important for retrieving relevant analogues, and that analogical mapping is based on role-filler bindings, relational similarity was the strongest predictor across all tasks. These results suggest that just like entity concepts, semantic relations have an internal structure that gives rise to typicality effects across a variety of tasks, which could provide constraints for testing competing theories of relational representation.

Calculating phenotypic similarity between genes using hierarchical structure data based on semantic similarity

Gene ◽  
2012 ◽  
Vol 497 (1) ◽  
pp. 58-65 ◽  
Author(s):  
Shanzhen Zhang ◽  
Zhiqiang Chang ◽  
Zhenqi Li ◽  
Huizi DuanMu ◽  
Zihui Li ◽  
...  
Keyword(s):  
Semantic Similarity ◽  
Hierarchical Structure ◽  
Structure Data ◽  
Phenotypic Similarity

scholarly journals The closer, the better? Processing relations between picture elements in historical paintings

2020 ◽  
Vol 13 (2) ◽  
Author(s):  
Manuela Glaser ◽  
Manuel Knoos ◽  
Stephan Schwan
Keyword(s):  
Eye Tracking ◽  
Cognitive Processing ◽  
Multimedia Learning ◽  
Semantic Relations ◽  
Temporal Distance ◽  
Spatial Distance ◽  
The West ◽  
Text Coherence ◽  
Subject Design ◽  
Better Than

The present eye-tracking study investigated how audio explanations influence perception and the cognitive processing of historical paintings. Spatially close and distant pairs of picture elements and their semantic relations were named in an audio text either immediately after each other or with descriptions of other elements in between. It was assumed that the number of backward fixation counts on the first of the two mentioned related picture elements should be higher if they are spatially close rather than spatially distant. There should also be more backward fixation counts if the elements are named temporally close rather than temporally distant. Similar predictions were made for the retention of these picture elements and their relations. A 2x2x2 within-subject design (n=36) with spatial distance (close vs. distant), temporal distance (close vs. distant) and painting (Leutze vs. West) revealed more background fixation counts for spatially close compared to spatially distant elements but just for the Leutze painting. Accordingly, the relations between the spatially close pairs were retained better than between the spatially distant pairs in the Leutze painting but vice versa for the West painting. The results are discussed with regard to the spatial contiguity principle of multimedia learning and research on text coherence.

scholarly journals The Adoption of US-Style Business Education in Mexico, 1945-2005

2012 ◽  
Vol 20 (1) ◽  
pp. 158 ◽  
Author(s):  
Bernardo Batiz-Lazo
Keyword(s):  
Higher Education ◽  
Mexico City ◽  
Hierarchical Structure ◽  
Business Education ◽  
Management Education ◽  
Business History ◽  
Institutional Setting ◽  
Font Size ◽  
Professional Managers ◽  
Education In Mexico

<span style="font-family: Times New Roman; font-size: small;"> </span><span style="font-family: Times New Roman; font-size: small;"> </span><p style="margin: 0cm 0cm 0pt;" class="MsoNormal"><span lang="EN-US" style="mso-ansi-language: EN-US;"><span style="font-size: small;"><span style="font-family: Times New Roman;">This article maps the idiosyncratic features in the development of graduate and postgraduate management education in Mexico City. The emergence of these degrees is partly in response to the globalization of higher education but also to the transformation of Mexican business organisations into a more hierarchical structure. The evolution of the institutional setting thus offers an indirect study of the appearance of professional managers in a region otherwise dominated by family run firms. As a result, this article contributes to contemporary Mexican business history by linking the forms of interaction between multinationals, indigenous businesses and management education.</span></span></span></p><span style="font-family: Times New Roman;"><span style="font-size: small;"> </span><span style="font-family: Times New Roman; font-size: small;"> </span></span>

Mining defining contexts to help structuring differential ontologies

Terminology ◽  
2005 ◽  
Vol 11 (1) ◽  
pp. 21-53 ◽  
Author(s):  
Véronique Malaisé ◽  
Pierre Zweigenbaum ◽  
Bruno Bachimont
Keyword(s):  
Semantic Similarity ◽  
Semantic Relation ◽  
Semantic Relations ◽  
Test Corpus ◽  
Future Work

In this paper, we present an experiment dealing with corpus-based construction of “differential ontologies”, which are organised according to semantic similarity and differential features. We argue that knowledge-rich defining contexts can be useful to help an ontology modeller in his task. We present a method, based on lexico-syntactic patterns, to spot such contexts in a corpus, then identify the terms they relate (definiendum and genus or “characteristics”) and the semantic relation that links them. We also show how potential co-hyponyms can be detected on the basis of shared words in their definiens. We evaluate the extracted defining sentences, semantic relations and co-hyponyms on a test corpus focusing on childhood and on an evaluation corpus about dietetics (both corpora are French). Definition extraction obtains 50% precision and recall of approximately 40%. Semantic relation identification reaches an average of 48% precision, and co-hyponyms 23.5%. We discuss the results of these experiments and conclude on perspectives for future work.

scholarly journals Penyusunan Bibliografi Beranotasi tentang Tan Malaka di UPT Perpustakaan Proklamator Bung Hatta

2020 ◽  
Vol 8 (2) ◽  
pp. 22
Author(s):  
Nofrianda Nofrianda ◽  
Malta Nelisa
Keyword(s):  
Information Retrieval ◽  
Data Collection ◽  
Information Needs ◽  
Annotated Bibliography ◽  
Writing Style ◽  
Font Size ◽  
Alphabetical Order ◽  
Numerical Notation ◽  
Selection Of

Abstract The writing of this paper aims to describe how the needs of visitors about the Tan Malaka collection, describe the process of making annotated Tan Malaka bibliography and describe the constraints and efforts in establishing the Tan Malaka annotated bibliography at the UPT Library of Bung Hatta Proklamator. This type of research is descriptive in that it explains the making of annotated bibliography about Tan Malaka at the Bung Hatta Library UPT. Data collection techniques through direct observation to the location and interviews and data collection by reading and studying sources in the form of books, literature, and teaching materials. Based on the data processed can be concluded as follows. First, the information needs of users about annotated bibliography about Tan Malaka, namely: education, reference materials and research. Second, making annotated bibliography about Tan Malaka has several stages, namely: (a) determining the title of the bibliography, because the availability of books is quite a lot and is a book that is in great demand; (b) collection of library materials or information retrieval, a book about Tan Malaka in the Bung Hatta Library UPT 34 titles; (c) selection of library materials, by checking one by one the Tan Malaka book collection; (d) classification or classification, carried out by using numerical notation sequence numbers; (e) creation of keywords, based on the book's title and the annotation of Tan Malaka's book; (f) index preparation, Tan Malaka's annotated biblographic index consists of author index, keywords and titles arranged in alphabetical order; (g) typing the text, using Times New Roman writing style, font size 12, and space 1; (h) examination of the final bibliographic manuscript. Third, the constraints and efforts in making annotated bibliography about Tan Malaka, namely: (a) the preparation of Tan Malaka's collection of books is irregular and the efforts made are doing stock taking; (b) the collection of Tan Malaka only has 1 copy and the effort to do is take action over the media.Keywords: annotated bibliography; Tan Malaka. 

scholarly journals Tag Clouds for Software Documents Visualization

2019 ◽  
Vol 3 (4) ◽  
Author(s):  
Ra'fat Ahmad Al-msie'deen
Keyword(s):  
New Method ◽  
Font Size ◽  
Visualization Technique ◽  
Software Developers ◽  
Alphabetical Order ◽  
Legacy Software ◽  
Tag Clouds ◽  
Tag Cloud

Legacy software documents are hard to understand and visualize. The tag cloud technique helps software developers to visualize the contents of software documents. A tag cloud is a well-known and simple visualization technique. This paper proposes a new method to visualize software documents, using a tag cloud. In this paper, tags visualize in the cloud based on their frequency in an alphabetical order. The most important tags are displayed with a larger font size. The originality of this method is that it visualizes the contents of JavaDoc as a tag cloud. To validate the JavaDocCloud method, it was applied to NanoXML case study, the results of these experiments display the most common and uncommon tags used in the software documents.

Study on Distributed Database Query Optimization

2014 ◽  
Vol 536-537 ◽  
pp. 540-544
Author(s):  
Feng Li ◽  
Hai Ying Wang
Keyword(s):  
Query Processing ◽  
Semantic Similarity ◽  
Distributed Algorithms ◽  
Distributed Database ◽  
Processing Algorithm ◽  
Spatial Distance ◽  
Mechanism Analysis ◽  
Distributed Query Processing ◽  
Advantages And Disadvantages ◽  
Distributed Query

This paper presents a heterogeneous sensor networks to improve query processing mechanism. Analysis of the advantages and disadvantages of centralized query processing algorithm is proposed based on the spatial distance distributed query processing algorithm based on semantic similarity and distributed query processing algorithms for query execution processes described. Use simulation to choose better coverage and semantic similarity by half, and centralized query processing algorithm, based on the spatial distance distributed algorithms, distributed algorithms and performance-based semantic distributed hybrid algorithm were compared.

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