BRIDGING STRUCTURE AND FEATURE REPRESENTATIONS IN GRAPH MATCHING

2012 ◽  
Vol 26 (05) ◽  
pp. 1260005 ◽  
Author(s):  
WAN-JUI LEE ◽  
VERONIKA CHEPLYGINA ◽  
DAVID M. J. TAX ◽  
MARCO LOOG ◽  
ROBERT P. W. DUIN
Keyword(s):  
Graph Matching ◽  
Structural Description ◽  
Dissimilarity Representation ◽  
Feature Representations ◽  
Bag Of Features ◽  
Attributed Graphs ◽  
Feature Based ◽  
Types Of Information ◽  
Essential Problem ◽  
Better Than

Structures and features are opposite approaches in building representations for object recognition. Bridging the two is an essential problem in pattern recognition as the two opposite types of information are fundamentally different. As dissimilarities can be computed for both the dissimilarity representation can be used to combine the two. Attributed graphs contain structural as well as feature-based information. Neglecting the attributes yields a pure structural description. Isolating the features and neglecting the structure represents objects by a bag of features. In this paper we will show that weighted combinations of dissimilarities may perform better than these two extremes, indicating that these two types of information are essentially different and strengthen each other. In addition we present two more advanced integrations than weighted combining and show that these may improve the classification performances even further.

Design, Development and Comparison of Heuristic Driven Algorithms Based on the Crossed Domain Products’ Reviews for User’s Summarization

2020 ◽  
Vol 13 (5) ◽  
pp. 884-892
Author(s):  
Sartaj Ahmad ◽  
Ashutosh Gupta ◽  
Neeraj Kumar Gupta
Keyword(s):  
Decision Making ◽  
Online Shopping ◽  
Recent Time ◽  
Design Development ◽  
Different Types ◽  
Feature Based ◽  
Use Of Internet ◽  
Day By Day ◽  
Better Than

Background: In recent time, people love online shopping but before any shopping feedbacks or reviews always required. These feedbacks help customers in decision making for buying any product or availing any service. In the country like India this trend of online shopping is increasing very rapidly because awareness and the use of internet which is increasing day by day. As result numbers of customers and their feedbacks are also increasing. It is creating a problem that how to read all reviews manually. So there should be some computerized mechanism that provides customers a summary without spending time in reading feedbacks. Besides big number of reviews another problem is that reviews are not structured. Objective: In this paper, we try to design, implement and compare two algorithms with manual approach for the crossed domain Product’s reviews. Methods: Lexicon based model is used and different types of reviews are tested and analyzed to check the performance of these algorithms. Results: Algorithm based on opinions and feature based opinions are designed, implemented, applied and compared with the manual results and it is found that algorithm # 2 is performing better than algorithm # 1 and near to manual results. Conclusion: Algorithm # 2 is found better on the different product’s reviews and still to be applied on other product’s reviews to enhance its scope. Finally, it will be helpful to automate existing manual process.

A new approach based on graph matching and evolutionary approach for sport scheduling problem

2020 ◽  
pp. 1-16
Author(s):  
Meriem Khelifa ◽  
Dalila Boughaci ◽  
Esma Aïmeur
Keyword(s):  
Graph Matching ◽  
State Of The Art ◽  
Travel Cost ◽  
Round Robin ◽  
New Approach ◽  
Traveling Tournament Problem ◽  
Significant Interest ◽  
National League ◽  
Better Than

The Traveling Tournament Problem (TTP) is concerned with finding a double round-robin tournament schedule that minimizes the total distances traveled by the teams. It has attracted significant interest recently since a favorable TTP schedule can result in significant savings for the league. This paper proposes an original evolutionary algorithm for TTP. We first propose a quick and effective constructive algorithm to construct a Double Round Robin Tournament (DRRT) schedule with low travel cost. We then describe an enhanced genetic algorithm with a new crossover operator to improve the travel cost of the generated schedules. A new heuristic for ordering efficiently the scheduled rounds is also proposed. The latter leads to significant enhancement in the quality of the schedules. The overall method is evaluated on publicly available standard benchmarks and compared with other techniques for TTP and UTTP (Unconstrained Traveling Tournament Problem). The computational experiment shows that the proposed approach could build very good solutions comparable to other state-of-the-art approaches or better than the current best solutions on UTTP. Further, our method provides new valuable solutions to some unsolved UTTP instances and outperforms prior methods for all US National League (NL) instances.

Feature-Based Design: 4 Hypotheses for Future CAD Systems

1993 ◽  
Author(s):  
David W. Rosen
Keyword(s):  
Future Research ◽  
Design Activity ◽  
Research Directions ◽  
Research Issues ◽  
Cad Systems ◽  
Feature Representations ◽  
Feature Based ◽  
Computer Based ◽  
Definition Of ◽  
Feature Based Design

Abstract Features are meaningful abstractions of geometry that engineers use to reason about components, products, and processes. For design activity, features are design primitives, serve as the basis for product representations, and can incorporate information relevant to life-cycle activities such as manufacturing. Research on feature-based design has matured to the point that results are being incorporated into commercial CAD systems. The intent here is to classify feature-based design literature to provide a solid historical basis for present research and to identify promising research directions that will affect computer-based design tools within the next few years. Applications of feature-based design and technologies of feature representations are reviewed. Open research issues are identified and put in the context of past and current work. Four hypotheses are proposed as challenges for future research: two on the existence of fundamental sub-feature elements and relationships for features, one that presents a new definition of design features, and one that argues for the successful development of concurrent engineering languages. Evidence for these hypotheses is provided from recent research results and from speculation about the future of feature-based design.

scholarly journals Effective Deep Memory Networks for Distant Supervised Relation Extraction

2017 ◽  
Author(s):  
Xiaocheng Feng ◽  
Jiang Guo ◽  
Bing Qin ◽  
Ting Liu ◽  
Yongjie Liu
Keyword(s):  
Relation Extraction ◽  
Training Data ◽  
Context Word ◽  
Neural Models ◽  
Attention Model ◽  
Memory Experiment ◽  
Feature Based ◽  
Real World Datasets ◽  
Major Attention ◽  
Better Than

Distant supervised relation extraction (RE) has been an effective way of finding novel relational facts from text without labeled training data. Typically it can be formalized as a multi-instance multi-label problem.In this paper, we introduce a novel neural approach for distant supervised (RE) with specific focus on attention mechanisms.Unlike the feature-based logistic regression model and compositional neural models such as CNN, our approach includes two major attention-based memory components, which is capable of explicitly capturing the importance of each context word for modeling the representation of the entity pair, as well as the intrinsic dependencies between relations.Such importance degree and dependency relationship are calculated with multiple computational layers, each of which is a neural attention model over an external memory. Experiment on real-world datasets shows that our approach performs significantly and consistently better than various baselines.

Learning the identity effect as an artificial language: bias and generalisation

Phonology ◽  
2013 ◽  
Vol 30 (2) ◽  
pp. 253-295 ◽  
Author(s):  
Gillian Gallagher
Keyword(s):  
Inductive Learning ◽  
Direct Reference ◽  
Explicit Representation ◽  
Artificial Grammar ◽  
Artificial Language ◽  
Language Bias ◽  
Root Node ◽  
Wilson Model ◽  
Feature Based ◽  
Better Than

The results of two artificial grammar experiments show that individuals learn a distinction between identical and non-identical consonant pairs better than an arbitrary distinction, and that they generalise the distinction to novel segmental pairs. These results have implications for inductive models of learning, because they necessitate an explicit representation of identity. While identity has previously been represented as root-node sharing in autosegmental representations (Goldsmith 1976, McCarthy 1986), or implicitly assumed to be a property that constraints can reference (MacEachern 1999, Coetzee & Pater 2008), the model of inductive learning proposed by Hayes & Wilson (2008) assumes strictly feature-based representations, and is unable to reference identity directly. This paper explores the predictions of the Hayes & Wilson model and compares it to a modification of the model where identity is represented (Colavin et al.2010). The results of both experiments support a model incorporating direct reference to identity.

Exploring the Determinants of Broadway Show Success

1998 ◽  
Vol 35 (3) ◽  
pp. 370-383 ◽  
Author(s):  
Srinivas K. Reddy ◽  
Vanitha Swaminathan ◽  
Carol M. Motley
Keyword(s):  
New York ◽  
Information Sources ◽  
New York Times ◽  
Differential Impact ◽  
Daily News ◽  
Types Of Information ◽  
Ticket Prices ◽  
The Impact ◽  
Selection Of ◽  
Better Than

This study investigates the determinants of success of an experiential good: Broadway shows. The authors focus on the sources and types of information used in the selection of an artistic event and discuss the impact of critics’ reviews on the length of a show's run and attendance. In addition, the authors empirically determine the influence of other variables, such as previews, newspaper advertising, ticket prices, show type, talent characteristics, and timing of opening. The results indicate that New York newspaper theater critics have a significant impact on the success of Broadway shows. It is also found that the newspaper critics have a differential impact, with the critic from the New York Times yielding nearly twice as much influence as critics from the Daily News or the New York Post. Theater critics, it appears, are not only predictors but influencers as well. Among the various show types, musicals appear to fare better than other categories of shows. Previews have a significant impact on the attendance, but not on the longevity, of Broadway shows. Advertising also has a significant impact on both longevity and attendance. However, the characteristics of the key talent do not have a consistently significant influence on show success. In addition, ticket prices do not have a significant relationship with either longevity or attendance. The results indicate that there is an overwhelming impact of information sources, particularly the influence of critics’ reviews, on the success of Broadway shows. The authors discuss the implications of these results for the theater industry.

scholarly journals No evidence for proactive suppression: Enhancement of explicitly cued distractor features

2021 ◽  
Author(s):  
Douglas A Addleman ◽  
Viola S. Störmer
Keyword(s):  
Visual Search ◽  
Feature Representations ◽  
Color Cues ◽  
Advance Knowledge ◽  
Better Than

Visual search benefits from advance knowledge of non-target features. However, it is unknown whether these negatively cued features are suppressed in advance (proactively) or during search (reactively). To test this, we presented color cues varying from trial-to-trial that predicted target or non-target colors. Experiment 1 (N=96) showed that both target and nontarget cues speeded search. To test whether attention proactively modified cued feature representations, in Experiment 2 (N=200), we interleaved color probe trials with search and had participants detect the color of a briefly presented ring that could either match the cued color or not. Interestingly, people detected both positively and negatively cued colors better than other colors, indicating that to-be-attended and to-be-ignored features were both proactively enhanced. These results demonstrate that nontarget features are not suppressed proactively, and instead support reactive accounts in which anticipated nontarget features are ignored via strategic enhancement.

scholarly journals Predictive Analytical Model for Microblogging Data Using Asset Bubble Modelling

2020 ◽  
Vol 14 (2) ◽  
pp. 108-118
Author(s):  
Srinidhi Hiriyannaiah ◽  
Siddesh G.M. ◽  
Srinivasa K.G.
Keyword(s):  
Social Media ◽  
Information Diffusion ◽  
Predictive Analytics ◽  
Heterogeneous Systems ◽  
Asset Bubble ◽  
Proposed Model ◽  
Different Types ◽  
Social Media Platforms ◽  
Types Of Information ◽  
Better Than

In recent days, social media plays a significant role in the ecosystem of the big data world and its different types of information. There is an emerging need for collection, monitoring, analyzing, and visualizing the different information from various social media platforms in different domains like businesses, public administration, and others. Social media acts as the representative with numerous microblogs for analytics. Predictive analytics of such microblogs provides insights into various aspects of the real-world entities. In this article, a predictive model is proposed using the tweets generated on Twitter social media. The proposed model calculates the potential of a topic in the tweets for the prediction purposes. The experiments were conducted on tweets of the regional election in India and the results are better than the existing systems. In the future, the model can be extended for analysis of information diffusion in heterogeneous systems.

Facial Expression Recognition Based on Monogenic Binary Coding

2014 ◽  
Vol 511-512 ◽  
pp. 437-440
Author(s):  
Xiao Xiao Xia ◽  
Zi Lu Ying ◽  
Wen Jin Chu
Keyword(s):  
Facial Expression ◽  
Facial Expression Recognition ◽  
Local Variation ◽  
Expression Recognition ◽  
Multi Scale ◽  
Linear Discrimination ◽  
Binary Coding ◽  
Japanese Female ◽  
Feature Based ◽  
Better Than

A new method based on Monogenic Binary Coding (MBC) is proposed for facial expression feature extraction and representation. Firstly, monogenic signal analysis is used to extract multi-scale magnitude, orientation and phase components. Secondly, Monogenic Binary Coding (MBC) is used to encode the monogenic local variation and intensity in local regions of each extracted component in each scale and local histograms are built. Then Blocked Fisher Linear Discrimination (BFLD) is used to reduce the dimensionality of histogram features and to enhance discrimination. Finally the three complementary components are fused for more effective facial expression recognition (FER). Experiment results on Japanese female expression database (JAFFE) show that the performance of the fusion method is even better than state-of-the-art local feature based FER methods such as Local Binary Pattern (LBP)+Sparse Representation (SRC), Local Phase Quantization (LPQ)+SRC ,etc.

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