Introduction to the special issue on cross-language algorithms and applications

With the increasingly global nature of our everyday interactions, the need for multilingual technologies to support efficient and efective information access and communication cannot be overemphasized. Computational modeling of language has been the focus of Natural Language Processing, a subdiscipline of Artificial Intelligence. One of the current challenges for this discipline is to design methodologies and algorithms that are cross-language in order to create multilingual technologies rapidly. The goal of this JAIR special issue on Cross-Language Algorithms and Applications (CLAA) is to present leading research in this area, with emphasis on developing unifying themes that could lead to the development of the science of multi- and cross-lingualism. In this introduction, we provide the reader with the motivation for this special issue and summarize the contributions of the papers that have been included. The selected papers cover a broad range of cross-lingual technologies including machine translation, domain and language adaptation for sentiment analysis, cross-language lexical resources, dependency parsing, information retrieval and knowledge representation. We anticipate that this special issue will serve as an invaluable resource for researchers interested in topics of cross-lingual natural language processing.Postprint (published version

SEMA4A: An ontology for emergency notification systems accessibility

This is the post-print version of the final paper published in Expert Systems with Applications. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2009 Elsevier B.V.Providing alert communication in emergency situations is vital to reduce the number of victims. Reaching this goal is challenging due to users’ diversity: people with disabilities, elderly and children, and other vulnerable groups. Notifications are critical when an emergency scenario is going to happen (e.g. a typhoon approaching) so the ability to transmit notifications to different kind of users is a crucial feature for such systems. In this work an ontology was developed by investigating different sources: accessibility guidelines, emergency response systems, communication devices and technologies, taking into account the different abilities of people to react to different alarms (e.g. mobile phone vibration as an alarm for deafblind people). We think that the proposed ontology addresses the information needs for sharing and integrating emergency notification messages over distinct emergency response information systems providing accessibility under different conditions and for different kind of users.Ministerio de Educación y Cienci

Argumentation Mining in User-Generated Web Discourse

The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways. (i) We deal with actual Web data and take up the challenges given by the variety of registers, multiple domains, and unrestricted noisy user-generated Web discourse. (ii) We bridge the gap between normative argumentation theories and argumentation phenomena encountered in actual data by adapting an argumentation model tested in an extensive annotation study. (iii) We create a new gold standard corpus (90k tokens in 340 documents) and experiment with several machine learning methods to identify argument components. We offer the data, source codes, and annotation guidelines to the community under free licenses. Our findings show that argumentation mining in user-generated Web discourse is a feasible but challenging task.Comment: Cite as: Habernal, I. & Gurevych, I. (2017). Argumentation Mining in User-Generated Web Discourse. Computational Linguistics 43(1), pp. 125-17

Weaving creativity into the Semantic Web: a language-processing approach

This paper describes a novel language processing ap- proach to the analysis of creativity and the development of a machine-readable ontology of creativity. The ontol- ogy provides a conceptualisation of creativity in terms of a set of fourteen key components or building blocks and has application to research into the nature of cre- ativity in general and to the evaluation of creative prac- tice, in particular. We further argue that the provision of a machine readable conceptualisation of creativity pro- vides a small, but important step towards addressing the problem of automated evaluation, ’the Achilles’ heel of AI research on creativity’ (Boden 1999)

Using Google Analytics, Voyant and Other Tools to Better Understand Use of Manuscript Collections at L. Tom Perry Special Collections

[Excerpt] Developing strategies for making data-driven, objective decisions for digitization and value-added processing. based on patron usage has been an important effort in the L. Tom Perry Special Collections (hereafter Perry Special Collections). In a previous study, the authors looked at how creating a matrix using both Web analytics and in-house use statistics could provide a solid basis for making decisions about which collections to digitize as well as which collections merited deeper description. Along with providing this basis for decision making, the study also revealed some intriguing insights into how our collections were being used and raised some important questions about the impact of description on both digital and physical usage. We have continued analyzing the data from our first study and that data forms the basis of the current study. It is helpful to review the major outcomes of our previous study before looking at what we have learned in this deeper analysis. In the first study, we utilized three sources of statistical data to compare two distinct data points (in-house use and online finding aid use) and determine if there were any patterns or other information that would help curators in the department make better decisions about the items or collections selected for digitization or value-added processing. To obtain our data points, we combined two data sources related to the in-person use of manuscript collections in the Perry Special Collections reading room and one related to the use of finding aids for manuscript collections made available online through the department’s Finding Aid database ( http://findingaid.lib.byu.edu/). We mapped the resulting data points into a four quadrant graph (see figure 1)

Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems