Call for Papers: Brain Inspired Natural Language Processing (BINLP)

[Erik Cambria]

Apologies for cross-posting.

Submissions are invited for a special session on Brain Inspired Natural Language Processing (BINLP) to be held within the 2012 International Conference on Brain Inspired Cognitive Systems (BICS), taking place from 11th to 14th July in Shenyang (China).

ABSTRACT
The ability to learn and understand natural language sounds obvious and natural to us but it is actually a daedal and multi-faceted process. The illusion of simplicity comes from the fact that, as each new group of skills matures, we build more layers on top of them and tend to forget about previous layers. Current attempts to perform automatic understanding of human language, e.g., textual entailment and machine reading, still suffer from numerous problems including inconsistencies, synonymy, polysemy, entity duplication and more, as they focus on a pure syntactical analysis of the information reaching the brain. If we want machines to literally understand natural language rather than merely simulating the ability to understand it, we need not only to investigate the synergies among the multi-modal and multi-sensorial data available to the machine, but also to go beyond a content-level analysis of natural language and aim for a concept- and context-level analysis, taking also the inevitably interactions with the environment into account. At the same time, as the natural language processing (NLP) techniques increase in realism and sensibility, more and more advanced evaluation procedures need to be explored and implemented to suitably assess the insightfulness of the developed technologies even in real application scenarios. The main aim of this BICS-12 Special Session is to examine the new frontiers of NLP by proposing brain-inspired techniques in fields such as computational intelligence, knowledge-based systems, multimedia (audio, video, textual) information processing, adaptive and transfer learning, in order to more efficiently extract useful information from human language which could lead to improved machine understanding and sustainable human-machine interfaces.

TOPICS
BINLP aims to provide an international forum for researchers in the field of natural language processing to share information on their latest investigations and their applications both in academic research areas and industrial sectors. The broader context of the Special Session comprehends AI, web mining, information retrieval, speech recognition, and opinion mining. Topics of interest include but are not limited to:
• Knowledge-based natural language processing
• Human language summarization and visualization
• Explicit and latent semantic analysis for natural language processing
• Time evolving human language analysis
• Computational linguistics
• Multi-domain natural language processing
• Multi-lingual natural language processing
• Multi-modal (spoken, typed, handwritten) natural language processing

TIMEFRAME
• February 15th, 2012: Due date for Special Session papers
• April 1st, 2012: Notification of paper acceptance to authors
• May 1st, 2012: Camera-ready of accepted papers
• July 11th, 2012: Special Session date

SUBMISSION AND PROCEEDINGS
Prospective authors are invited to submit full-length papers (6-8 pages normally and 10 pages maximum) by the submission deadline through the online submission system. The submission of a paper implies that the paper is original and has not been submitted under review or copyright protected elsewhere and will be presented by an author if accepted. All submitted papers will be refereed by experts in the field based on the criteria of originality, significance, quality, and clarity. The authors of accepted papers will have an opportunity to revise their papers and take consideration of the referees’ comments and suggestions. All papers accepted by and presented at BICS 2012 will be published by Springer as multiple volumes of Lecture Notes in Artificial Intelligence which will be indexed by EI and ISTP. Selected papers will be published in special issues of several SCI journals.

ORGANIZERS
• Erik Cambria, National University of Singapore (Singapore)
• Stefano Squartini, Marche Polytechnic University (Italy)
• Amir Hussain, University of Stirling (UK)
• Newton Howard, MIT Media Laboratory (USA)

For up-to-date information about this CFP, please visit http://sentic.net/2011/10/10/binlp
___________________________
Erik Cambria
康文涵

Research Scientist
Cognitive Science Programme

Tel: +65 6516 5752
Web: http://sentic.net
Email: cam...@nus.edu.sg
Twitter: http://twitter.com/senticnet
Facebook: http://facebook.com/senticnet

Temasek Laboratories
National University of Singapore
5A Engineering Drive 1, Singapore 117411

[Erik Cambria]

Apologies for cross-posting.

Submissions are invited for the ACM KDD Workshop on Issues of Sentiment Discovery and Opinion Mining (http://sentic.net/wisdom).

ABSTRACT
The exponential growth of the Social Web is virally infecting more and more critical business processes such as customer support and satisfaction, brand and reputation management, product design and marketing. Because of this global trend, web users already evolved from the era of social relationships, in which they began to get connected and started to share contents, to the era of social functionality, in which they started using social networks as the main platform for communication and dissemination of information. Today, web users are going through the era of social colonization, in which every experience on the Web can be social (e.g., Facebook Like button), and are getting ready for the era of social context, in which web contents will be highly targeted and personalized. The final stage of such Social Web evolution is the so called era of social commerce, in which communities will define future products and services. In such context, the research field of sentiment analysis, which has already been rapidly growing in the last decade, is destined to become more and more important for Web and business dynamics.
WISDOM aims to explore how the wisdom of the crowds is affecting (and will affect) the evolution of the Web and of businesses gravitating around it. In particular, the ACM KDD workshop explores two different stages of sentiment analysis: the former focusing on the identification of opinionated text over the Web, the latter focusing on the classification of such text either in terms of polarity detection or emotion recognition.

TOPICS
The workshop will provide an international forum for both researchers and entrepreneurs working in the field of opinion mining to share information on their latest investigations in social information retrieval and their applications in academic research areas and industrial sectors. The broader context of the workshop comprehends AI, Semantic Web, information retrieval, web mining, and natural language processing (NLP). In addition to paper presentations, an invited talk by Professor Bing Liu will stress the interdisciplinary challenges of opinion mining and sentiment analysis. Topics of interest include but are not limited to:
• Sentiment identification & classification
• Knowledge-based opinion mining
• Sentiment summarization & visualization
• Entity discovery & extraction
• Opinion aggregation
• Opinion search & retrieval
• Time evolving sentiment analysis
• Opinion spam detection
• Comparative opinion analysis
• Topic detection & trend discovery
• Psychological models for sentiment analysis
• Multilingual opinion mining
• Social ranking
• Social network analysis
• Influence, trust & privacy analysis
• Business intelligence applications

INVITED SPEAKER
Bing Liu is a professor of Computer Science at University of Illinois at Chicago (UIC). He received his PhD in Artificial Intelligence from the University of Edinburgh. Before joining UIC, he was with the National University of Singapore. His current research interests include opinion mining and sentiment analysis, Web mining, and data mining. He has published extensively in leading conferences and journals in these fields. He has also written a textbook titled “Web Data Mining: Exploring Hyperlinks, Contents and Usage Data” published by Springer. The second edition of the book came out in July 2011. On professional services, Liu has served as program chairs of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), IEEE International Conference on Data Mining (ICDM), ACM Conference on Web Search and Data Mining (WSDM), SIAM Conference on Data Mining (SDM), ACM Conference on Information and Knowledge Management (CIKM), and Pacific Asia Conference on Data Mining (PAKDD). Additionally, he has also served as associate editors of IEEE Transactions on Knowledge and Data Engineering (TKDE), Journal of Data Mining and Knowledge Discovery (DMKD), and SIGKDD Explorations, and is on the editorial boards of several other journals.

TIMEFRAME
• May 8th, 2012: Due date for workshop papers
• June 8th, 2012, 2011: Notification of paper acceptance to authors
• June 18th, 2012, 2011: Camera-ready of accepted papers
• August 12th, 2012: Workshop date

PROGRAM COMMITTEE
• Alexandra Balahur, University of Alicante (Spain)
• Sandra Baldassarri, University of Zaragoza (Spain)
• Catherine Baudin, eBay Research Labs (USA)
• Eva Cerezo, University of Zaragoza (Spain)
• Praphul Chandra, HP Labs India (India)
• Amitava Das, Norwegian University of Science and Technology (Norway)
• Dipankar Das, Jadavpur University (India)
• Sergio Decherchi, Italian Institute of Technology (Italy)
• Rafael Del Hoyo, Aragon Institute of Technology (Spain)
• Tariq Durrani, University of Strathclyde (UK)
• Paolo Gastaldo, University of Genoa (Italy)
• Marco Grassi, Marche Polytechnic University (Italy)
• Minlie Huang, Tsinghua University (China)
• Isabelle Hupont, Aragon Institute of Technology (Spain)

• Amir Hussain, University of Stirling (UK)

• Raymond Lau, City University of Hong Kong (Hong Kong)
• Shixia Liu, Microsoft Research Asia (China)
• Saif Mohammad, National Research Council (Canada)
• Samaneh Moghaddam, Simon Fraser University (Canada)
• Muaz Niazi, Bahria University (Pakistan)
• Bjoern Schuller, Technical University of Munich (Germany)

• Stefano Squartini, Marche Polytechnic University (Italy)

• Kam-Fai Wong, Chinese University of Hong Kong (Hong Kong)
• Rui Xia, Nanjing University of Science and Technology (China)
• Lei Zhang, University of Illinois at Chicago (USA)

ORGANIZERS
• Erik Cambria, National University of Singapore (Singapore)

• Yongzheng Zhang, eBay Research Labs (USA)
• Yunqing Xia, Tsinghua University (China)

• Newton Howard, MIT Media Laboratory (USA)

__________________________________
Dr. Erik Cambria (康文涵)

Research Scientist

[Erik Cambria]

Apologies for cross-posting.

Submissions are invited for an IEEE Intelligent Systems special issue on Concept-Level Opinion and Sentiment Analysis (http://computer.org/intelligent/cfp2).

ABSTRACT
Opinions play a primary role in decision-making processes. Whenever people need to make a choice, they are naturally inclined to hear others’ opinions. In particular, when the decision involves consuming valuable resources, such as time and/or money, people strongly rely on their peers’ past experiences. Just a few years ago, the main sources for collecting such information were friends, acquaintances and, in some cases, specialized magazines or websites. The passage from a read-only to a read-write Web has provided people with new tools that allow them to create and share, in a timely and cost-efficient way, their own contents, ideas, and opinions with virtually millions of people connected to the World Wide Web. The opportunity to capture the opinions of the general public about social events, political movements, company strategies, marketing campaigns, and product preferences has raised more and more interest both in the scientific community, for the exciting emergent challenges, and in the business world, for the remarkable fallouts in marketing and financial market prediction. Mining opinions and sentiments from natural language, however, is an extremely difficult task: it involves a deep understanding of most of the explicit and implicit, regular and irregular, syntactical and semantic rules of a language. Existing approaches mainly rely on parts of text in which opinions and sentiments are explicitly expressed such as polarity terms, affect words, and their co-occurrence frequencies. However, opinions and sentiments are often conveyed implicitly through latent semantics, which make purely syntactical approaches ineffective. In this light, this special issue focuses on the introduction, presentation, and discussion of novel approaches to opinion mining and sentiment analysis that are not entirely based on domain-dependent corpora but also on general-purpose semantic knowledge bases. The main motivation for the issue, in particular, is to go beyond a mere word-level analysis of text and provide novel concept-level approaches to opinion mining and sentiment analysis that allow a more efficient passage from (unstructured) textual information to (structured) machine-processible data, in potentially any domain.

TOPICS
Articles are thus invited in areas such as AI, the Semantic Web, knowledge-based systems, and adaptive and transfer learning for research on opinion and sentiment retrieval and analysis. Potential topics include:
• Opinion and sentiment summarization and visualization
• Explicit and latent semantic analysis for opinion and sentiment mining
• Knowledge base construction and integration with opinion and sentiment analysis
• Transfer learning of opinion and sentiment with knowledge bases
• Time-evolving opinion and sentiment analysis
• Corpora and resources for opinion and sentiment analysis
• Multimodal sentiment analysis
• Multidomain and cross-domain evaluation
• Multilingual sentiment analysis and reuse of knowledge bases

TIMEFRAME
July 1st, 2012: Paper submission deadline
September 16th, 2012: Notification of acceptance
November 11th, 2012: Final manuscript due
March/April, 2013: Publication

SUBMISSION AND PROCEEDINGS
The special issue will consist of papers on novel methods and techniques for building and using semantic knowledge bases in the field of opinion mining and sentiment analysis. Besides the specified topics of interest, the special issue also welcomes papers on specific application domains of sentiment analysis—for example, social data mining, influence networks, customer experience management, computer-mediated human-human communication, social media marketing, multimedia management, personalization and persuasion, enterprise feedback management, human-agent, -computer and -robot interaction, intelligent user interfaces, patient opinion mining, surveillance, and art. Submissions should be 3,000 to 5,400 words (counting a standard figure or table as 200 words) and should follow IEEE Intelligent Systems style and presentation guidelines. The manuscripts cannot have been published or be currently submitted for publication elsewhere. We strongly encourage submissions that include audio, video, and community content, which will be featured on the IEEE Computer Society Web site along with the accepted papers.

ORGANIZERS
• Erik Cambria, National University of Singapore (Singapore)

• Bjoern Schuller, Technical University of Munich (Germany)

• Bing Liu, University of Illinois at Chicago (USA)
• Haixun Wang, Microsoft Research Asia (China)
• Catherine Havasi, MIT Media Laboratory (USA)
__________________________________
Erik Cambria, PhD
康文涵
Research Scientist

Temasek Laboratories
Cognitive Science Programme

National University of Singapore
5A Engineering Drive 1, Singapore 117411