Description

Abstract

The primary information units in a newspaper are the articles. How to segment a newspaper

page into individual articles and to recover the reading order of each article, namely

newspaper article reconstruction, is known to be challenging due to the complexity of the

multi-article page layout. In this paper, we propose a novel article reconstruction approach by

solving a series of subtasks: grouping the article bodies, detecting the reading order,

associating the title-body pairs and linking article parts scattered in multiple pages. We

formulate reading order detection as a traveling salesman problem (TSP), and employ the

Max-Min Ant System (MMAS) to solve it. Furthermore, a level-based pheromone

mechanism is introduced to improve the efficiency of standard MMAS. Moreover, in sharp

contrast to the existing methods, we perform the first two subtasks of article reconstruction in

reverse order, that is, we detect the reading order of the text blocks first and then use the

content continuity implicitly specified in the reading order to aggregate text blocks of the

same article.