We propose a new neural network architecture, called Simple Recurrent Temporal-Difference Networks (SR-TDNs), that learns to predict future observations in partially observable en...
Abstract. This paper shows how Wikipedia and the semantic knowledge it contains can be exploited for document clustering. We first create a concept-based document representation b...
Anna Huang, David N. Milne, Eibe Frank, Ian H. Wit...
In this paper, we present an algorithm for learning a generative model of natural language sentences together with their formal meaning representations with hierarchical structure...
Wei Lu, Hwee Tou Ng, Wee Sun Lee, Luke S. Zettlemo...
- There is continuing research interest in comparison of the complexity of problems within the class NP-Complete. This paper examines the representational power of conjunctive norm...
In this paper we deal with the problem of addition of new documents in collection when documents are represented in lower dimensional space by concept indexing. Concept indexing i...