Textual Article Clustering in Newspaper Pages

Aiello, Marco; Pegoretti, Andrea

doi:10.1080/08839510600903858

Cited by 11 publications

(3 citation statements)

References 11 publications

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“…On the left side is represented the basic entityrelationship (ER) model used to design the database and, on the right side, the schematic diagram shows how the data was organized after the conclusion of the content analysis research. It should be pointed out that no text processing technique, such as text-clustering algorithms (Aiello and Pegoretti 2006), was employed during the analysis of the data. The outcomes of the content research were expressed by means of production rules.…”

Section: Methods Implementationmentioning

confidence: 99%

Structuring and Modeling Data for Representing the Behavior of Agents in the Governance of the Brazilian Financial System

Streit

Borenstein

2009

Applied Artificial Intelligence

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This article proposes a method to collect and structure data in order to model the behavior of agents in an agent-based simulation model. This model aims to study the regulatory governance of the Brazilian financial system. In this article, the regulatory governance is understood as a phenomenon that results from several interactions and transactions among all actors that influence or are influenced by the activities of the regulation policies. The study focuses on the short-term interest rates and incorporates behavioral aspects and no-explicit interests of social and economical agents. The developed method integrates content analysis research andin-depth interviews to model the agents' behavior by means of fuzzy logic rules. It provides systematic collection and interpretation of data produced in textual form as well as knowledge from experts. The results of the model validation have shown that this approach contributes to the development of a methodology for the modeling and representation of agent behavior in social applied simulation models.

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Section: Methods Implementationmentioning

confidence: 99%

Structuring and Modeling Data for Representing the Behavior of Agents in the Governance of the Brazilian Financial System

Streit

Borenstein

2009

Applied Artificial Intelligence

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“…Few authors [3], [10] have also worked on article extraction based on similarity of text from the text blocks generated from segmenting newspaper images. Furmaniak [10] identified paragraphs in the newspaper page and then measured similarity is measured between neighboring OCR'ed paragraphs.…”

Section: Related Workmentioning

confidence: 99%

Newspaper Article Extraction Using Hierarchical Fixed Point Model

Bansal¹,

Chaudhury²,

Roy³

et al. 2014

2014 11th IAPR International Workshop on Document Analysis Systems

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This paper presents a novel learning based framework to extract articles from newspaper images using a Fixed-Point Model. The input to the system comprises blocks of text and graphics, obtained using standard image processing techniques. The fixed point model uses contextual information and features of each block to learn the layout of newspaper images and attains a contraction mapping to assign a unique label to every block. We use a hierarchical model which works in two stages. In the first stage, a semantic label (heading, sub-heading, text-blocks, image and caption) is assigned to each segmented block. The labels are then used as input to the next stage to group the related blocks into news articles. Experimental results show the applicability of our algorithm in newspaper labeling and article extraction.

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“…A set of rules on layout understanding were created based on visual information such as distance, size, color, etc. Opposite to the aforementioned techniques relying merely on the visual information, Aiello et al [14] introduced a semantic information based method to determine the reading order. A lexical analysis the technique was adopted to rank candidate reading orders based on partof-speech (POS) probability.…”

Section: Research Gapmentioning

confidence: 99%

A Novel Approach for Document Retrieval System with User Preferences

Kaur¹,

Bhatla²

2014

IJCA

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This paper proposes a method for Document Retrieval Systems. The document retrieval system finds information to given criteria by matching text record (documents) against user queries. The results generated from information retrieval system must have user preferences. Each user has its own perspectives and cultural context of each word or when the user is searching for highly specific, focussed topic. The probabilistic ranking based on graphic Bayesian statistics is associated with a Kuhn munkres algorithm for it to be really successful to group similar documents. The probabilistic ranking based Kuhn munkres algorithm uses the graphical model such as Bayesian statistics with Bayesian's theorem to find the probability of documents for more relevant results.

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Textual Article Clustering in Newspaper Pages

Cited by 11 publications

References 11 publications

Structuring and Modeling Data for Representing the Behavior of Agents in the Governance of the Brazilian Financial System

Structuring and Modeling Data for Representing the Behavior of Agents in the Governance of the Brazilian Financial System

Newspaper Article Extraction Using Hierarchical Fixed Point Model

A Novel Approach for Document Retrieval System with User Preferences

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