1,721,243 research outputs found
AI*IA 2007: artificial intelligence and human-oriented computing: 10th Congress of the Italian association for artificial intelligence, Rome, Italy, September 10-13, 2007, Proceedings
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Context-aware Models for Twitter Sentiment Analysis
No full textRecent works on Sentiment Analysis over Twitter are tied to the idea that the sentiment can
be completely captured after reading an incoming tweet. However, tweets are filtered through
streams of posts, so that a wider context, e.g. a topic, is always available. In this work, the
contribution of this contextual information is investigated for the detection of the polarity of
tweet messages. We modeled the polarity detection problem as a sequential classification task over
streams of tweets. A Markovian formulation of the Support Vector Machine discriminative model
has been here adopted to assign the sentiment polarity to entire sequences. The experimental
evaluation proves that sequential tagging better embodies evidence about the contexts and is
able to increase the accuracy of the resulting polarity detection process. These evidences are
strengthened as experiments are successfully carried out over two different languages: Italian
and English. Results are particularly interesting as the approach is flexible and does not rely on
any manually coded resources
Harmonization and development of resources and tools for Italian natural language processing within the PARLI project
No full textThe papers collected in this volume are selected as a sample of the progress in Natural Language Processing (NLP) performed within the Italian NLP community and especially attested by the PARLI project. PARLI (Portale per l’Accesso alle Risorse in Lingua Italiana) is a project partially funded by the Ministero Italiano per l’Università e la Ricerca (PRIN 2008) from 2008 to 2012 for monitoring and fostering the harmonic growth and coordination of the activities of Italian NLP. It was proposed by various teams of researchers working in Italian universities and research institutions. According to the spirit of the PARLI project, most of the resources and tools created within the project and here described are freely distributed and they did not terminate their life at the end of the project itself, hoping they could be a key factor in future development of computational linguistics
Robust Spoken Language Understanding for House Service Robots
Full text linkService robotics has been growing significantly in thelast years, leading to several research results and to a numberof consumer products. One of the essential features of theserobotic platforms is represented by the ability of interactingwith users through natural language. Spoken commands canbe processed by a Spoken Language Understanding chain, inorder to obtain the desired behavior of the robot. The entrypoint of such a process is represented by an Automatic SpeechRecognition (ASR) module, that provides a list of transcriptionsfor a given spoken utterance. Although several well-performingASR engines are available off-the-shelf, they operate in a generalpurpose setting. Hence, they may be not well suited in therecognition of utterances given to robots in specific domains. Inthis work, we propose a practical yet robust strategy to re-ranklists of transcriptions. This approach improves the quality of ASRsystems in situated scenarios, i.e., the transcription of roboticcommands. The proposed method relies upon evidences derivedby a semantic grammar with semantic actions, designed tomodel typical commands expressed in scenarios that are specificto human service robotics. The outcomes obtained throughan experimental evaluation show that the approach is able toeffectively outperform the ASR baseline, obtained by selectingthe first transcription suggested by the AS
A context based model for sentiment analysis in twitter for the italian language
Full text linkStudi recenti per la Sentiment
Analysis in Twitter hanno tentato di creare
modelli per caratterizzare la polarit ́a di
un tweet osservando ciascun messaggio
in isolamento. In realt`a, i tweet fanno
parte di conversazioni, la cui natura pu`o
essere sfruttata per migliorare la qualit`a
dell’analisi da parte di sistemi automatici.
In (Vanzo et al., 2014) `e stato proposto un
modello basato sulla classificazione di sequenze
per la caratterizzazione della polarit`
a dei tweet, che sfrutta il contesto in
cui il messaggio `e immerso. In questo lavoro,
si vuole verificare l’applicabilit`a di
tale metodologia anche per la lingua Italiana.Recent works on Sentiment
Analysis over Twitter leverage the idea
that the sentiment depends on a single
incoming tweet. However, tweets are
plunged into streams of posts, thus making
available a wider context. The contribution
of this information has been recently
investigated for the English language by
modeling the polarity detection as a sequential
classification task over streams of
tweets (Vanzo et al., 2014). Here, we want
to verify the applicability of this method
even for a morphological richer language,
i.e. Italian
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Using Semantic Models for Robust Natural Language Human Robot Interaction
No full textWhile robotic platforms are moving from industrial to consumer applications, the need of flexible and intuitive interfaces becomes more critical and the capability of governing the variability of human language a strict requirement. Grounding of lexical expressions, i.e. mapping words of a user utterance to the perceived entities of a robot operational scenario, is particularly critical. Usually, grounding proceeds by learning how to associate objects categorized in discrete classes (e.g. routes or sets of visual patterns) to linguistic expressions. In this work, we discuss how lexical mapping functions that integrate Distributional Semantics representations and phonetic metrics can be adopted to robustly automate the grounding of language expressions into the robotic semantic maps of a house environment. In this way, the pairing between words and objects into a semantic map facilitates the grounding without the need of an explicit categorization. Comparative measures demonstrate the viability of the proposed approach and the achievable robustness, quite crucial in operational robotic settings
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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