Multidocument Summarization of Engineering Papers Based on Macro- and Microstructure

2011 ◽  
Vol 11 (1) ◽  
Author(s):  
Jiaming Zhan ◽  
Ying Liu ◽  
Han Tong Loh
Keyword(s):  
Experimental Study ◽  
Classification Problem ◽  
Equivalence Classes ◽  
Automatic Summarization ◽  
Categorization Task ◽  
Rhetorical Structure ◽  
Evaluation Scores ◽  
Multidocument Summarization ◽  
Multiple Documents

This paper focuses on automatic summarization of multiple engineering papers. A summarization approach based on documents’ macro- and microstructure has been proposed. The macrostructure consists of a list of ranked topics from engineering papers. Topics are discovered by extracting and grouping frequently appearing word sequences into equivalence classes. Hence, the macrostructure symbolically presents the topical links in different papers. Meanwhile, the microstructure is defined as the rhetorical structure within a single paper. The identification of microstructure is approached as a classification problem. Each sentence in a paper is automatically labeled with one of the predefined rhetorical categories. Unlike existing summarization methods that first separate documents into nonoverlapping clusters and then summarize each cluster individually, our approach aims to summarize multiple documents according to the characteristics suggested at macro- and microstructure levels. The experimental study showed that our proposed approach outperformed peer systems in terms of recall-oriented understudy for gisting evaluation scores and readers’ responsiveness. In an independent manual categorization task using the summaries generated by our approach and peer systems, we also performed better in terms of precision and recall.

scholarly journals Automatic Summarization from Multiple Documents

2009 ◽  
Author(s):  
Γεώργιος Γιαννακόπουλος
Keyword(s):  
Automatic Summarization ◽  
Multiple Documents

scholarly journals Gender and Handedness Prediction from Offline Handwriting Using Convolutional Neural Networks

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Ángel Morera ◽  
Ángel Sánchez ◽  
José Francisco Vélez ◽  
Ana Belén Moreno
Keyword(s):  
Neural Networks ◽  
Experimental Study ◽  
Convolutional Neural Networks ◽  
Deep Neural Networks ◽  
Classification Problem ◽  
Gender Classification ◽  
Network Configuration ◽  
Classification Problems ◽  
Design Complexity ◽  
Average Accuracy

Demographic handwriting-based classification problems, such as gender and handedness categorizations, present interesting applications in disciplines like Forensic Biometrics. This work describes an experimental study on the suitability of deep neural networks to three automatic demographic problems: gender, handedness, and combined gender-and-handedness classifications, respectively. Our research was carried out on two public handwriting databases: the IAM dataset containing English texts and the KHATT one with Arabic texts. The considered problems present a high intrinsic difficulty when extracting specific relevant features for discriminating the involved subclasses. Our solution is based on convolutional neural networks since these models had proven better capabilities to extract good features when compared to hand-crafted ones. Our work also describes the first approach to the combined gender-and-handedness prediction, which has not been addressed before by other researchers. Moreover, the proposed solutions have been designed using a unique network configuration for the three considered demographic problems, which has the advantage of simplifying the design complexity and debugging of these deep architectures when handling related handwriting problems. Finally, the comparison of achieved results to those presented in related works revealed the best average accuracy in the gender classification problem for the considered datasets.

Answering engineers' questions using semantic annotations

2007 ◽  
Vol 21 (2) ◽  
pp. 155-171 ◽  
Author(s):  
SANGHEE KIM ◽  
ROB H. BRACEWELL ◽  
KEN M. WALLACE
Keyword(s):  
Question Answering ◽  
Structure Theory ◽  
Preliminary Evaluation ◽  
Retrieval Performance ◽  
Rhetorical Structure ◽  
Semantic Annotations ◽  
Recent Trends ◽  
Multiple Documents

Question–answering (QA) systems have proven to be helpful, especially to those who feel uncomfortable entering keywords, sometimes extended with search symbols such as +, *, and so forth. In developing such systems, the main focus has been on the enhanced retrieval performance of searches, and recent trends in QA systems center on the extraction of exact answers. However, when their usability was evaluated, some users indicated that they found it difficult to accept the answers because of the absence of supporting context and rationale. Current approaches to address this problem include providing answers with linking paragraphs or with summarizing extensions. Both methods are believed to be sufficient to answer questions seeking the names of objects or quantities that have only a single answer. However, neither method addresses the situation when an answer requires the comparison and integration of information appearing in multiple documents or in several places in a single document. This paper argues that coherent answer generation is crucial for such questions, and that the key to this coherence is to analyze texts to a level beyond sentence annotations. To demonstrate this idea, a prototype has been developed based on rhetorical structure theory, and a preliminary evaluation has been carried out. The evaluation indicates that users prefer to see the extended answers that can be generated using such semantic annotations, provided that additional context and rationale information are made available.

scholarly journals If-Then Planning Helps School-Aged Children to Ignore Attractive Distractions

2011 ◽  
Vol 42 (1) ◽  
pp. 39-47 ◽  
Author(s):  
Frank Wieber ◽  
Antje von Suchodoletz ◽  
Tobias Heikamp ◽  
Gisela Trommsdorff ◽  
Peter M. Gollwitzer
Keyword(s):  
Experimental Study ◽  
Response Times ◽  
Implementation Intentions ◽  
Self Control ◽  
Ongoing Task ◽  
Categorization Task ◽  
School Aged Children ◽  
Field Of Vision ◽  
Language Competency ◽  
Goal Intentions

Can children improve shielding an ongoing task from distractions by if-then planning (i.e., by forming implementation intentions)? In an experimental study, the situational and personal limits of action control by distraction-inhibiting implementation intentions (“If a distraction comes up, then I will ignore it!”) were tested by comparing them to simple goal intentions (“I will ignore distractions!”). Goal intentions were sufficient to successfully ignore distractions of low attractiveness. In the presence of moderately and highly attractive distractions, as well as a distraction presented out of the children’s sight, however, only implementation intentions improved children’s task shielding, as indicated by faster response times in an ongoing categorization task and shorter periods of looking at highly attractive distractions presented out of their field of vision. These findings held true regardless of the children’s temperament and language competency. Implications for research on planning and developmental research on self-control are discussed.

scholarly journals Homotopy and Isotopy Properties of Topological Spaces

1961 ◽  
Vol 13 ◽  
pp. 167-176 ◽  
Author(s):  
Sze-Tsen Hu
Keyword(s):  
Topological Space ◽  
Equivalence Relation ◽  
Classification Problem ◽  
Equivalence Classes ◽  
Topological Classification ◽  
Topological Spaces ◽  
The Family ◽  
Important Notion

The most important notion in topology is that of ahomeomorphism f: X→Yfrom a topological spaceXonto a topological spaceY. If a homeomorphism f:X→Yexists, then the topological spaces X andFare said to behomeomorphic(ortopologically equivalent), in symbols,X ≡ Y.The relation ≡ among topological spaces is obviously reflexive, symmetric, and transitive; hence it is an equivalence relation. For an arbitrary familyFof topological spaces, this equivalence relation ≡ divides /Mnto disjoint equivalence classes called thetopology typesof the familyF. Then, the main problem in topology is the topological classification problem formulated as follows.The topological classification problem:Given a familyF oftopological spaces, find an effective enumeration of the topology types of the familyFand exhibit a representative space in each of these topology types.

scholarly journals Rhetorical Structure Theory for polarity estimation: An experimental study

2014 ◽  
Vol 94 ◽  
pp. 135-147 ◽  
Author(s):  
José M. Chenlo ◽  
Alexander Hogenboom ◽  
David E. Losada
Keyword(s):  
Experimental Study ◽  
Structure Theory ◽  
Rhetorical Structure
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