Learning domain-specific sentiment lexicon with supervised sentiment-aware LDA

Frontiers in Artificial Intelligence and Applications, v. 263 entitled: ECAI 2014: 21st European Conference on Artificial Intelligence, 18-22 August 2014, Prague, Czech Republic - Including Prestigious Applications of Intelligent Systems (PAIS 2014)Analyzing and understanding people's sentiments towards different topics has become an interesting task due to the explosion of opinion-rich resources. In most sentiment analysis applications, sentiment lexicons play a crucial role, to be used as metadata of sentiment polarity. However, most previous works focus on discovering general-purpose sentiment lexicons. They cannot capture domain-specific sentiment words, or implicit and connotative sentiment words that are seemingly objective. In this paper, we propose a supervised sentiment-aware LDA model (ssLDA). The model uses a minimal set of domain-independent seed words and document labels to discover a domain-specific lexicon, learning a lexicon much richer and adaptive to the sentiment of specific document. Experiments on two publicly-available datasets (movie reviews and Obama-McCain debate dataset) show that our model is effective in constructing a comprehensive and high-quality domain-specific sentiment lexicon. Furthermore, the resulting lexicon significantly improves the performance of sentiment classification tasks. © 2014 The Authors and IOS Press.published_or_final_versio

Algorithms for Manipulating Sequential Allocation

Sequential allocation is a simple and widely studied mechanism to allocate indivisible items in turns to agents according to a pre-specified picking sequence of agents. At each turn, the current agent in the picking sequence picks its most preferred item among all items having not been allocated yet. This problem is well-known to be not strategyproof, i.e., an agent may get more utility by reporting an untruthful preference ranking of items. It arises the problem: how to find the best response of an agent? It is known that this problem is polynomially solvable for only two agents and NP-complete for arbitrary number of agents. The computational complexity of this problem with three agents was left as an open problem. In this paper, we give a novel algorithm that solves the problem in polynomial time for each fixed number of agents. We also show that an agent can always get at least half of its optimal utility by simply using its truthful preference as the response

Lattice-based biclustering using Partition Pattern Structures

International audienceIn this work we present a novel technique for exhaustive bicluster enumeration using formal concept anal-ysis (FCA). Particularly, we use pattern structures (an ex-tension of FCA dealing with complex data) to mine similar row/column biclusters, a specialization of biclustering when attribute values have coherent variations. We show how bi-clustering can benefit from the FCA framework through its ro-bust theoretical description and efficient algorithms. Finally, we evaluate our bicluster mining approach w.r.t. a standard biclustering technique showing very good results in terms of bicluster quality and performance

Computing Query Answering With Non-Monotonic Rules: A Case Study of Archaeology Qualitative Spatial Reasoning

International audienceThis paper deals with querying ontology-based knowledge bases equipped with non-monotonic rules through a case study within the framework of Cultural Heritage. It focuses on 3D underwater surveys on the Xlendi wreck which is represented by an OWL2 knowledge base with a large dataset. The paper aims at improving the interactions between the archaeologists and the knowledge base providing new queries that involve non-monotonic rules in order to perform qualitative spatial reasoning. To this end, the knowledge base initially represented in OWL2-QL is translated into an equivalent Answer Set Programming (ASP) program and is enriched with a set of non-monotonic ASP rules suitable to express default and exceptions. An ASP query answering approach is proposed and implemented. Furthermore due to the increased expressiveness of non-monotonic rules it provides spatial reasoning and spatial relations between artifacts query answering which is not possible with query answering languages such as SPARQL and SQWRL

Social Relationships for Designing Agent Interaction in JADE

Abstract—Current agent platforms do not provide agents the means for reasoning about expected behaviours during interactions. This lack is due to the absence of design primitives to explicitly shape interaction patterns as first-class resources. This work presents 2COMM4JADE, a framework based on JADE and CArtAgO platforms that allows definition of social relationships among parties, represented by social commitments, decoupled from the agent design itself. I

Using Formal Methods for Autonomous Systems: Five Recipes for Formal Verification

Formal Methods are mathematically-based techniques for software design and engineering, which enable the unambiguous description of and reasoning about a system's behaviour. Autonomous systems use software to make decisions without human control, are often embedded in a robotic system, are often safety-critical, and are increasingly being introduced into everyday settings. Autonomous systems need robust development and verification methods, but formal methods practitioners are often asked: Why use Formal Methods for Autonomous Systems? To answer this question, this position paper describes five recipes for formally verifying aspects of an autonomous system, collected from the literature. The recipes are examples of how Formal Methods can be an effective tool for the development and verification of autonomous systems. During design, they enable unambiguous description of requirements; in development, formal specifications can be verified against requirements; software components may be synthesised from verified specifications; and behaviour can be monitored at runtime and compared to its original specification. Modern Formal Methods often include highly automated tool support, which enables exhaustive checking of a system's state space. This paper argues that Formal Methods are a powerful tool for the repertoire of development techniques for safe autonomous systems, alongside other robust software engineering techniques.Comment: Accepted at Journal of Risk and Reliabilit