scholarly journals Semantic association ranking schemes for information retrieval applications using term association graph representation

Sadhana ◽  
2015 ◽  
Vol 40 (6) ◽  
pp. 1793-1819 ◽  
Author(s):  
K VENINGSTON ◽  
R SHANMUGALAKSHMI ◽  
V NIRMALA
Keyword(s):  
Information Retrieval ◽  
Graph Representation ◽  
Semantic Association ◽  
Association Graph

A survey of tag clouds as tools for information retrieval and content representation

2020 ◽  
pp. 147387162096663
Author(s):  
Úrsula Torres Parejo ◽  
Jesús R Campaña ◽  
M Amparo Vila ◽  
Miguel Delgado
Keyword(s):  
Information Retrieval ◽  
Structural Properties ◽  
The Internet ◽  
Original Text ◽  
Semantic Association ◽  
Tag Clouds ◽  
Tag Cloud ◽  
Content Representation ◽  
Visual Interfaces

Tag clouds are tools that have been widely used on the Internet since their conception. The main applications of these textual visualizations are information retrieval, content representation and browsing of the original text from which the tags are generated. Despite the extensive use of tag clouds, their enormous popularity and the amount of research related to different aspects of them, few studies have summarized their most important features when they work as tools for information retrieval and content representation. In this paper we present a summary of the main characteristics of tag clouds found in the literature, such as their different functions, designs and negative aspects. We also present a summary of the most popular metrics used to capture the structural properties of a tag cloud generated from the query results, as well as other measures for evaluating the goodness of the tag cloud when it works as a tool for content representation. The different methods for tagging and the semantic association processes in tag clouds are also considered. Finally we give a list of alternative for visual interfaces, which makes this study a useful first help for researchers who want to study the content representation and information retrieval interfaces in greater depth.

scholarly journals Time-Sync Video Tag Extraction Using Semantic Association Graph

2019 ◽  
Vol 13 (4) ◽  
pp. 1-24 ◽  
Author(s):  
Wenmain Yang ◽  
Kun Wang ◽  
Na Ruan ◽  
Wenyuan Gao ◽  
Weijia Jia ◽  
...  
Keyword(s):  
Semantic Association ◽  
Association Graph

scholarly journals Semantic Component Association within Object Classes Based on Convex Polyhedrons

2020 ◽  
Vol 10 (8) ◽  
pp. 2641 ◽  
Author(s):  
Petra Đurović ◽  
Ivan Vidović ◽  
Robert Cupec
Keyword(s):  
Physical Properties ◽  
Real Time ◽  
Weight Distribution ◽  
Semantic Association ◽  
Object Class ◽  
Geometrical Arrangement ◽  
Semantic Component ◽  
Association Graph ◽  
Object Parts ◽  
Robotic Tasks

Most objects are composed of semantically distinctive parts that are more or less geometrically distinctive as well. Points on the object relevant for a certain robot operation are usually determined by various physical properties of the object, such as its dimensions or weight distribution, and by the purpose of object parts. A robot operation defined for a particular part of a representative object can be transferred and adapted to other instances of the same object class by detecting the corresponding components. In this paper, a method for semantic association of the object’s components within the object class is proposed. It is suitable for real-time robotic tasks and requires only a few previously annotated representative models. The proposed approach is based on the component association graph and a novel descriptor that describes the geometrical arrangement of the components. The method is experimentally evaluated on a challenging benchmark dataset.

Crowdsourced time-sync video tagging using semantic association graph

2017 ◽  
Author(s):  
Wenmian Yang ◽  
Na Ruan ◽  
Wenyuan Gao ◽  
Kun Wang ◽  
Wensheng Ran ◽  
...  
Keyword(s):  
Semantic Association ◽  
Association Graph

scholarly journals Graph Edit Distance Learning via Modeling Optimum Matchings with Constraints

2021 ◽  
Author(s):  
Yun Peng ◽  
Byron Choi ◽  
Jianliang Xu
Keyword(s):  
Edit Distance ◽  
State Of The Art ◽  
Graph Representation ◽  
Heuristic Methods ◽  
Graph Edit Distance ◽  
Specific Loss ◽  
Association Graph ◽  
One To One ◽  
The One ◽  
Matching Constraints

Graph edit distance (GED) is a fundamental measure for graph similarity analysis in many real applications. GED computation has known to be NP-hard and many heuristic methods are proposed. GED has two inherent characteristics: multiple optimum node matchings and one-to-one node matching constraints. However, these two characteristics have not been well considered in the existing learning-based methods, which leads to suboptimal models. In this paper, we propose a novel GED-specific loss function that simultaneously encodes the two characteristics. First, we propose an optimal partial node matching-based regularizer to encode multiple optimum node matchings. Second, we propose a plane intersection-based regularizer to impose the one-to-one constraints for the encoded node matchings. We use the graph neural network on the association graph of the two input graphs to learn the cross-graph representation. Our experiments show that our method is 4.2x-103.8x more accurate than the state-of-the-art methods on real-world benchmark graphs.

MIVCN: Multimodal interaction video captioning network based on semantic association graph

2021 ◽  
Author(s):  
Ying Wang ◽  
Guoheng Huang ◽  
Lin Yuming ◽  
Haoliang Yuan ◽  
Chi-Man Pun ◽  
...  
Keyword(s):  
Multimodal Interaction ◽  
Semantic Association ◽  
Video Captioning ◽  
Association Graph

Demonstration of the Use of Tape-Recorded Information from a High Vacuum Electron Microscope

1969 ◽  
Vol 27 ◽  
pp. 218-219
Author(s):  
Richard E. Hartman ◽  
Roberta S. Hartman ◽  
Peter L. Ramos
Keyword(s):  
Information Retrieval ◽  
Electron Microscope ◽  
Magnetic Tape ◽  
High Vacuum ◽  
Data Retrieval ◽  
Electronic Information ◽  
Electronic Data ◽  
Subsequent Processing ◽  
Continuous Record

We have long felt that some form of electronic information retrieval would be more desirable than conventional photographic methods in a high vacuum electron microscope for various reasons. The most obvious of these is the fact that with electronic data retrieval the major source of gas load is removed from the instrument. An equally important reason is that if any subsequent analysis of the data is to be made, a continuous record on magnetic tape gives a much larger quantity of data and gives it in a form far more satisfactory for subsequent processing.

Stain contamination and embedding in electron microscopy

1986 ◽  
Vol 44 ◽  
pp. 50-53
Author(s):  
Hilton H. Mollenhauer
Keyword(s):  
Electron Microscopy ◽  
Information Retrieval ◽  
Epoxy Resins ◽  
Image Contrast ◽  
Sample Preservation ◽  
Factors Associated ◽  
Amount Of Information ◽  
Electron Microscopical ◽  
Contrast Information

Many factors (e.g., resolution of microscope, type of tissue, and preparation of sample) affect electron microscopical images and alter the amount of information that can be retrieved from a specimen. Of interest in this report are those factors associated with the evaluation of epoxy embedded tissues. In this context, informational retrieval is dependant, in part, on the ability to “see” sample detail (e.g., contrast) and, in part, on tue quality of sample preservation. Two aspects of this problem will be discussed: 1) epoxy resins and their effect on image contrast, information retrieval, and sample preservation; and 2) the interaction between some stains commonly used for enhancing contrast and information retrieval.

Sign in / Sign up

Export Citation Format

Share Document