Abstract

Intelligent Information Access techniques attempt to overcome the limitations of current search devices by providing personalized information items and product/service recommendations. They normally utilize direct or indirect user input and facilitate the information search and decision processes, according to user needs, preferences and usage patterns. Recent developments at the intersection of Information Retrieval, Information Filtering, Machine Learning, User Modelling, Natural Language Processing and Human- Computer Interaction offer novel solutions that empower users to go beyond single-session lookup tasks and that aim at serving the more complex requirement: “Tell me what I don’t know that I need to know”. Information filtering systems, specifically recommender systems, have been revolutionizing the way information seekers find what they want, because they effectively prune large information spaces and help users in selecting items that best meet their needs and preferences. Recommender systems rely strongly on the use of various machine learning tools and algorithms for learning how to rank, or predict user evaluation, of items. Information Retrieval systems, on the other hand, also attempt to address similar filtering and ranking problems for pieces of information such as links, pages, and documents. But they generally focus on the development of global retrieval techniques, often neglecting individual user needs and preferences. The book aims to investigate current developments and new insights into methods, techniques and technologies for intelligent information access from a multidisciplinary perspective. It comprises six chapters authored by participants in the research event Intelligent Information Access, held in Cagliari (Italy) in December 2008. In Chapter 1, Enhancing Conversational Access to Information through a Socially Intelligent Agent, Berardina De Carolis, Irene Mazzotta and Nicole Novielli emphasize the role of Embodied Conversational Agents (ECAs) as a natural interaction metaphor for personalized and context-adapted access to information. They propose a scalable architecture for the development of ECAs able to exhibit an emotional state and/or social signs. VI Preface The automatic detection of emotions in text is the problem investigated in Chapter 2, Annotating and Identifying Emotions in Text, by Carlo Strapparava and Rada Mihalcea. The authors describe the “Affective Text” task, presented at SEMEVAL- 2007. The task focused on classifying emotions in news headlines, and was intended to explore the connection between emotions and lexical semantics. After illustrating the data set, the rationale of the task and a brief description of the participating systems, several experiments on the automatic annotation of emotions in text are presented. The practical applications of the task are very important. Consider for example opinion mining and market analysis, affective computing, natural language interfaces for e-learning environments or educational games. Personalization of the ranking computed by search engines and recommender systems is the main topic of Chapter 3, Improving Ranking by Respecting the Multidimensionality and Uncertainty of User Preferences, by Bettina Berendt and Veit Koppen. The research question addressed by the authors is whether system ranking is the “right ranking” for the user, based on the context in which she/he operates. A general conceptualization of the ranking-evaluation task is proposed: the comparison between the ranking generated by a computational system, and the “ user’s ideal ranking”. Eight challenges to this simple model are discussed, leading to the conclusion that approaches for dealing with multidimensional, and often only partial, preference orders are required and that randomness could be a beneficial feature of system rankings. In Chapter 4, Hotho reviews

Autore Pugliese

• Semeraro Giovanni , De Gemmis Marco

Tutti gli autori

• SEMERARO G.;de GEMMIS M.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2010

ISSN

1613-0073

ISBN

978-3-642-13999-4

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

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Numero di citazioni Scopus

3

Ultimo Aggiornamento Citazioni

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Settori ERC

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Codici ASJC

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