In this work, we propose an approach to index Deep Convolutional Neural Network Features to support efficient content-based retrieval on large image databases. To this aim, we have converted the these features into a textual form, to index them into an inverted index by means of Lucene. In this way, we were able to set up a robust retrieval system that combines full-text search with content-bas...

This study employs a novel method of Web content extraction and analysis to investigate the evolving competitive landscape in an important business-to-consumer (B2C) area: travel and tourism. Findings from a comprehensive Web mining endeavor and a supplier survey shed light on the effectiveness of tourism Web sites. Important dimensions of the automated measurement are ease of navigation, inter...

This paper describes the free software component JEmblazoner. JEmblazoner is a Java-based user interface for Content-based Image Retrieval (CBIR) in databases of coats of arms images. JEmblazoner allows to create coats of arms images from textual descriptions (socalled Blazons) that can be used as input for CBIR queries. In CBIR image databases are queried by qualitative features without the as...

Textual entailment has been proposed as a unifying generic framework for modeling language variability and semantic inference in different Natural Language Processing (NLP) tasks. This paper presents a novel statistical method for recognizing Chinese textual entailment in which lexical, syntactic with semantic matching features are combined together. In order to solve the problems of syntactic ...

The use of visual features in text-based ad-hoc image retrieval is challenging. Visual and textual information have so far been treated equally in terms of their properties and combined with weighting mechanisms for balancing their contributions to the ranking. The use of visual and textual information in a single retrieval system sometimes limits its applicability due to the lack of modularity...

Recognizing stances in ideological debates is a relatively new and challenging problem in opinion mining. While previous work mainly focused on text modality, in this paper, we try to recognize stances from both text and acoustic modalities, where how to derive more representative textual and acoustic features still remains the research problem. Inspired by the promising performances of neural ...

Online user comments contain valuable user opinions. Comments vary greatly in quality and detecting high quality comments is a subtask of opinion mining and summarization research. Finding attentive comments that provide some reasoning is highly valuable in understanding the user’s opinion particularly in sociopolitical opinion mining and aids policy makers, social organizations or government s...

This paper discusses the recognition of textual entailment in a text-hypothesis pair by applying a wide variety of lexical measures. We consider that the entailment phenomenon can be tackled from three general levels: lexical, syntactic and semantic. The main goals of this research are to deal with this phenomenon from a lexical point of view, and achieve high results considering only such kind...

This paper describes our participation to the ImageCLEF 2016 scalable concept image annotation main task and Text Illustration teaser. Regarding image annotation, we focused on better localizing the detected features. For this, we identified the saliency of the image to collect a list of potential interesting places into the image. We also added a specific human attribute detector that boosted ...

Crowdsourcing represents an innovative approach that allows companies to engage a diverse network of people over the internet and use their collective creativity, expertise, or workforce for completing tasks that have previously been performed by dedicated employees or contractors. However, the process of reviewing and filtering the large amount of solutions, ideas, or feedback submitted by a c...