Spoken document retrieval experiments with IR-n system

This paper describes the first participation of IR-n system at Spoken Document Retrieval, focusing on the experiments we made before participation and showing the results we obtained. IR-n system is an Information Retrieval system based on passages and the recognition of sentences to define them. So, the main goal of this experiment is to adapt IR-n system to the spoken document structure by means of the utterance splitter and the overlapping passage technique allowing to match utterances and sentences.

Using WordNet relations and semantic classes in information retrieval tasks

In this paper we explore the use of semantic classes in an existing information retrieval system in order to improve its results. Thus, we use two different ontologies of semantic classes (WordNet domain and Basic Level Concepts) in order to re-rank the retrieved documents and obtain better recall and precision. Finally, we implement a new method for weighting the expanded terms taking into account the weights of the original query terms and their relations in WordNet with respect to the new ones (which have demonstrated to improve the results). The evaluation of these approaches was carried out in the CLEF Robust-WSD Task, obtaining an improvement of 1.8% in GMAP for the semantic classes approach and 10% in MAP employing the WordNet term weighting approach.

Towards a unified framework for opinion retrieval, mining and summarization

The exponential increase of subjective, user-generated content since the birth of the Social Web, has led to the necessity of developing automatic text processing systems able to extract, process and present relevant knowledge. In this paper, we tackle the Opinion Retrieval, Mining and Summarization task, by proposing a unified framework, composed of three crucial components (information retrieval, opinion mining and text summarization) that allow the retrieval, classification and summarization of subjective information. An extensive analysis is conducted, where different configurations of the framework are suggested and analyzed, in order to determine which is the best one, and under which conditions. The evaluation carried out and the results obtained show the appropriateness of the individual components, as well as the framework as a whole. By achieving an improvement over 10% compared to the state-of-the-art approaches in the context of blogs, we can conclude that subjective text can be efficiently dealt with by means of our proposed framework.

Using IR-n for information retrieval of Genomics Track

Nowadays there is a big amount of biomedical literature which uses complex nouns and acronyms of biological entities thus complicating the task of retrieval specific information. The Genomics Track works for this goal and this paper describes the approach we used to take part of this track of TREC 2007. As this is the first time we participate in this track, we configurated a new system consisting of the following diferenciated parts: preprocessing, passage generation, document retrieval and passage (with the answer) extraction. We want to call special attention to the textual retrieval system used, which was developed by the University of Alicante. Adapting the resources for the propouse, our system has obtained precision results over the mean and median average of the 66 official runs for the Document, Aspect and Passage2 MAP; and in the case of Passage MAP we get nearly the median and mean value. We want to emphasize we have obtained these results without incorporating specific information about the domain of the track. For the future, we would like to further develop our system in this direction.

A multimodal genre recognition prototype

In this paper, a multimodal and interactive prototype to perform music genre classification is presented. The system is oriented to multi-part files in symbolic format but it can be adapted using a transcription system to transform audio content in music scores. This prototype uses different sources of information to give a possible answer to the user. It has been developed to allow a human expert to interact with the system to improve its results. In its current implementation, it offers a limited range of interaction and multimodality. Further development aimed at full interactivity and multimodal interactions is discussed.

Question answering and multi-search engines in geo-temporal information retrieval

In this paper we present a complete system for the treatment of both geographical and temporal dimensions in text and its application to information retrieval. This system has been evaluated in both the GeoTime task of the 8th and 9th NTCIR workshop in the years 2010 and 2011 respectively, making it possible to compare the system to contemporary approaches to the topic. In order to participate in this task we have added the temporal dimension to our GIR system. The system proposed here has a modular architecture in order to add or modify features. In the development of this system, we have followed a QA-based approach as well as multi-search engines to improve the system performance.

Polarimetric Response of Rice Fields at C-Band: Analysis and Phenology Retrieval

A set of ten RADARSAT-2 images acquired in fully polarimetric mode over a test site with rice fields in Seville, Spain, has been analyzed to extract the main features of the C-band radar backscatter as a function of rice phenology. After observing the evolutions versus phenology of different polarimetric observables and explaining their behavior in terms of scattering mechanisms present in the scene, a simple retrieval approach has been proposed. This algorithm is based on three polarimetric observables and provides estimates from a set of four relevant intervals of phenological stages. The validation against ground data, carried out at parcel level for a set of six stands and up to nine dates per stand, provides a 96% rate of coincidence. Moreover, an equivalent compact-pol retrieval algorithm has been also proposed and validated, providing the same performance at parcel level. In all cases, the inversion is carried out by exploiting a single satellite acquisition, without any other auxiliary information.

ATTOS: Análisis de Tendencias y Temáticas a través de Opiniones y Sentimientos

El proyecto ATTOS centra su actividad en el estudio y desarrollo de técnicas de análisis de opiniones, enfocado a proporcionar toda la información necesaria para que una empresa o una institución pueda tomar decisiones estratégicas en función a la imagen que la sociedad tiene sobre esa empresa, producto o servicio. El objetivo último del proyecto es la interpretación automática de estas opiniones, posibilitando así su posterior explotación. Para ello se estudian parámetros tales como la intensidad de la opinión, ubicación geográfica y perfil de usuario, entre otros factores, para facilitar la toma de decisiones. El objetivo general del proyecto se centra en el estudio, desarrollo y experimentación de técnicas, recursos y sistemas basados en Tecnologías del Lenguaje Humano (TLH), para conformar una plataforma de monitorización de la Web 2.0 que genere información sobre tendencias de opinión relacionadas con un tema.

Application of Text Summarization techniques to the Geographical Information Retrieval task

Automatic Text Summarization has been shown to be useful for Natural Language Processing tasks such as Question Answering or Text Classification and other related fields of computer science such as Information Retrieval. Since Geographical Information Retrieval can be considered as an extension of the Information Retrieval field, the generation of summaries could be integrated into these systems by acting as an intermediate stage, with the purpose of reducing the document length. In this manner, the access time for information searching will be improved, while at the same time relevant documents will be also retrieved. Therefore, in this paper we propose the generation of two types of summaries (generic and geographical) applying several compression rates in order to evaluate their effectiveness in the Geographical Information Retrieval task. The evaluation has been carried out using GeoCLEF as evaluation framework and following an Information Retrieval perspective without considering the geo-reranking phase commonly used in these systems. Although single-document summarization has not performed well in general, the slight improvements obtained for some types of the proposed summaries, particularly for those based on geographical information, made us believe that the integration of Text Summarization with Geographical Information Retrieval may be beneficial, and consequently, the experimental set-up developed in this research work serves as a basis for further investigations in this field.

Noise-tolerance feasibility for restricted-domain Information Retrieval systems

Information Retrieval systems normally have to work with rather heterogeneous sources, such as Web sites or documents from Optical Character Recognition tools. The correct conversion of these sources into flat text files is not a trivial task since noise may easily be introduced as a result of spelling or typeset errors. Interestingly, this is not a great drawback when the size of the corpus is sufficiently large, since redundancy helps to overcome noise problems. However, noise becomes a serious problem in restricted-domain Information Retrieval specially when the corpus is small and has little or no redundancy. This paper devises an approach which adds noise-tolerance to Information Retrieval systems. A set of experiments carried out in the agricultural domain proves the effectiveness of the approach presented.

International conference paper presentations: A multimodal analysis to determine effectiveness

International conference presentations represent one of the biggest challenges for academics using English as a Lingua Franca (ELF). This paper aims to initiate exploration into the multimodal academic discourse of oral presentations, including the verbal, written, non-verbal material (NVM) and body language modes. It offers a Systemic Functional Linguistic (SFL) and multimodal framework of presentations to enhance mixed-disciplinary ELF academics' awareness of what needs to be taken into account to communicate effectively at conferences. The model is also used to establish evaluation criteria for the presenters' talks and to carry out a multimodal discourse analysis of four well-rated 20-min talks, two from the technical sciences and two from the social sciences in a workshop scenario. The findings from the analysis and interviews indicate that: (a) a greater awareness of the mode affordances and their combinations can lead to improved performances; (b) higher reliance on the visual modes can compensate for verbal deficiencies; and (c) effective speakers tend to use a variety of modes that often overlap but work together to convey specific meanings. However, firm conclusions cannot be drawn on the basis of workshop presentations, and further studies on the multimodal analysis of ‘real conferences’ within specific disciplines are encouraged.

Retrieval of phenological stages of onion fields during the first year of growth by means of C-band polarimetric SAR measurements

The phenological stages of onion fields in the first year of growth are estimated using polarimetric observables and single-polarization intensity channels. Experiments are undertaken on a time series of RADARSAT-2 C-band full-polarimetric synthetic aperture radar (SAR) images collected in 2009 over the Barrax region, Spain, where ground truth information about onion growth stages is provided by the European Space Agency (ESA)-funded agricultural bio/geophysical retrieval from frequent repeat pass SAR and optical imaging (AgriSAR) field campaign conducted in that area. The experimental results demonstrate that polarimetric entropy or copolar coherence when used jointly with the cross-polarized intensity allows unambiguously distinguishing three phenological intervals.

The orchestration of modes and EFL audio-visual comprehension: A multimodal discourse analysis of vodcasts

This thesis explores the role of multimodality in language learners’ comprehension, and more specifically, the effects on students’ audio-visual comprehension when different orchestrations of modes appear in the visualization of vodcasts. Firstly, I describe the state of the art of its three main areas of concern, namely the evolution of meaning-making, Information and Communication Technology (ICT), and audio-visual comprehension. One of the most important contributions in the theoretical overview is the suggested integrative model of audio-visual comprehension, which attempts to explain how students process information received from different inputs. Secondly, I present a study based on the following research questions: ‘Which modes are orchestrated throughout the vodcasts?’, ‘Are there any multimodal ensembles that are more beneficial for students’ audio-visual comprehension?’, and ‘What are the students’ attitudes towards audio-visual (e.g., vodcasts) compared to traditional audio (e.g., audio tracks) comprehension activities?’. Along with these research questions, I have formulated two hypotheses: Audio-visual comprehension improves when there is a greater number of orchestrated modes, and students have a more positive attitude towards vodcasts than traditional audios when carrying out comprehension activities. The study includes a multimodal discourse analysis, audio-visual comprehension tests, and students’ questionnaires. The multimodal discourse analysis of two British Council’s language learning vodcasts, entitled English is GREAT and Camden Fashion, using ELAN as the multimodal annotation tool, shows that there are a variety of multimodal ensembles of two, three and four modes. The audio-visual comprehension tests were given to 40 Spanish students, learning English as a foreign language, after the visualization of vodcasts. These comprehension tests contain questions related to specific orchestrations of modes appearing in the vodcasts. The statistical analysis of the test results, using repeated-measures ANOVA, reveal that students obtain better audio-visual comprehension results when the multimodal ensembles are constituted by a greater number of orchestrated modes. Finally, the data compiled from the questionnaires, conclude that students have a more positive attitude towards vodcasts in comparison to traditional audio listenings. Results from the audio-visual comprehension tests and questionnaires prove the two hypotheses of this study.

The importance of promoting multimodal teaching in the foreign language classroom for the acquisition of social competences: practical examples

This article analyses the way in which the subject English Language V of the degree English Studies (English Language and Literature) combines the development of the five skills (listening, speaking, reading, writing and interacting) with the use of multimodal activities and resources in the teaching-learning process so that students increase their motivation and acquire different social competences that will be useful for the labour market such as communication, cooperation, leadership or conflict management. This study highlights the use of multimodal materials (texts, videos, etc.) on social topics to introduce cultural aspects in a language subject and to deepen into the different social competences university students can acquire when they work with them. The study was guided by the following research questions: how can multimodal texts and resources contribute to the development of the five skills in a foreign language classroom? What are the main social competences that students acquire when the teaching-learning process is multimodal? The results of a survey prepared at the end of the academic year 2015-2016 point out the main competences that university students develop thanks to multimodal teaching. For its framework of analysis, the study draws on the main principles of visual grammar (Kress & van Leeuwen, 2006) where students learn how to analyse the main aspects in multimodal texts. The analysis of the different multimodal activities described in the article and the survey reveal that multimodality is useful for developing critical thinking, for bringing cultural aspects into the classroom and for working on social competences. This article will explain the successes and challenges of using multimodal texts with social content so that students can acquire social competences while learning content. Moreover, the implications of using multimodal resources in a language classroom to develop multiliteracies will be observed.

Multimodal analysis of a sample of political posters in Ireland during and after the Celtic Tiger

The aim of this research paper is to analyse the key political posters made for the campaigns of Irish political party Fianna Fáil framed in the Celtic Tiger (1997-2008) and post-Celtic Tiger years (2009-2012). I will then focus on the four posters of the candidate in the elections that took place in 1997, 2002, 2007 and 2011 with the intention of observing first how the leader is represented, and later on pinpointing the similarities and possible differences between each. This is important in order to observe the main linguistic and visual strategies used to persuade the audience to vote that party and to highlight the power of the politician. Critical discourse analysis tools will be helpful to identify the main discursive strategies employed to persuade the Irish population to vote in a certain direction. Van Leeuwen’s (2008) social actor theory will facilitate the understanding of how participants are represented in the corpus under analysis. Finally, the main tools of Kress and van Leeuwen’s visual grammar (2006) will be applied for the analysis of the images. The study reveals that politicians are represented in a consistently positive way, with status and formal appearance so that people are persuaded to vote for the party they represent because they trust them as political leaders. The study, thus, points out that the poster is a powerful tool used in election campaigns to highlight the power of political parties.