User-contributed content represents a valuable information source provided one can make sense of the large amounts of unstructured data. This work focusses on geospatial content and specifically on travelblogs. Users writing stories about their trips and related experiences effectively provide geospatial information albeit in narrative form. Identifying this geospatial aspect of the texts by me...

In this paper, we propose a new text recognition model based on measuring the visual similarity of text and predicting the content of the unlabeled texts. First a Siamese network is trained with deep supervision on a labeled training dataset. This network projects texts into a similarity manifold. The Deeply Supervised Siamese network learns visual similarity of texts. Then a K-nearest neighbor...

dependence on computers and internet has given birth to digital literacy. however, research into its influences on the reading process is still in its infancy. to fill the gap, this study was designed to investigate the ways in which text presentation mode (paper vs. digital) affects reading comprehension, as well as reading attitudes. to this end, a sample of 30 male and female english major s...

This paper discusses an approach to planning the content of instructional texts. The research is based on a corpus study of 15 French procedural texts ranging from step-by-step device manuals to general artistic procedures. The approach taken starts from an AI task planner building a task representation, from which semantic carriers are selected. The most appropriate RST relations to communicat...

Collaborative writing is the process by which more than one author contributes to the content of a document. Although, multi-synchronous collaboration is very efficient in reducing task completion time, it is well known for producing documents of poor-quality content. Most existing collaborative writing environments do not really check the logical arrangement of documents portions (i.e. sentenc...

The purpose of this paper is to describe a multi-agent system for collaborative multimedia information retrieval in an electronic retailing application. We use content-based information (CBIR) retrieval for multimedia data including full-texts and images. Content-based image retrieval deals with retrieving data based on automatic content analysis as opposed to manual annotations, such as metada...

Users express their feelings about an entity of a specific topic in a free way using short texts on social networks. Sentiment analysis, also known as opinion mining, focuses on examining these texts to determine their polarity. This article presents an approach to the mining of opinions based on topics from Twitter texts in Spanish. The main objective is to decide the polarity of a text, deter...

Traditional image classification relies on text information such as tags, which requires a lot of human effort to annotate them. Therefore, recent work focuses more on training the classifiers directly on visual features extracted from image content. The performance of content-based classification is improving steadily, but it is still far below users’ expectation. Moreover, in a web environmen...

This paper describes an approach to automatically align fragments of texts of two documents in different languages. A text fragment is a list of continuous sentences and an aligned pair of fragments consists of two fragments in two documents, which are content-wise related. Cross-lingual similarity between fragments of texts is estimated based on models of divergence from randomness. A set of a...