A Concept for Control and Program Based on the Semantic Space Model

The most important mechanism of the computer is that various functions are implemented based on programs stored in it. Programs are developed by program languages implementing functions of models. One of the efficient methods to construct a model is to construct it by semantic computation models. Using semantic computation models, we can construct a model in a semantic space. In this paper, we present a mechanism to execute models presented by the semantic spaces. We have presented a mechanism to implement combinational and sequential logic computations based on the semantic space model. The combinational and sequential logic computations are the basic functions in computer systems. However, we still need a control mechanism like that in computers. In this paper, we present a control mechanism based on the semantic space model and some of execution examples. The most important contribution of this paper is that we first present a concept for control and program based on the semantic space model. In order to demonstrate the efficiency of the proposed mechanism, we performed a demonstration experiment. In the experiment, an agent is constructed for unmanned ground vehicle control with the control mechanism. A video camera is used to determine the position of the vehicle and obstacles on the road. The control signals, including “turn left,” “turn right,” “go ahead” and “stop” outputted from the agent are used to demonstrate the efficiency of the mechanism.

A New Hypred Improved Method for Measuring Concept Semantic Similarity in WordNet

Computing semantic similarity between concepts is an important issue in natural language processing, artificial intelligence, information retrieval and knowledge management. The measure of computing concept similarity is a fundament of semantic computation. In this paper, we analyze typical semantic similarity measures and note Wu and Palmer’s measure which does not distinguish the similarities between nodes from a node to different nodes of the same level. Then, we synthesize the advantages of measure of path-based and IC-based, and propose a new hybrid method for measuring semantic similarity. By testing on a fragment of WordNet hierarchical tree, the results demonstrate the proposed method accurately distinguishes the similarities between nodes from a node to different nodes of the same level and overcome the shortcoming of the Wu and Palmer’s measure

Semantics in Universal Grammar

This chapter considers the part semantics plays in Universal Grammar. The core cases considered incude principles of semantic computation, the realisation of arguments and the place of truth and reference, especially with respect to anaphora. The chapter highlights the cenral part of Merge in the construction of structure and meaning and extends it to the construction of lexical items and the lexicon where attention is paid not only to the way lexical items are constructed (by Merge) but also the ways in which they are taken apart in derivations again by Merge (self-Merge).

Scalar implicatures in non-monotonic environments

Scalar implicatures (SIs) have been traditionally analyzed as pragmatic inferences that arise after semantic computation. Recent studies, however, have presented various challenges to this classic analysis; for instance, it has been claimed that SIs can be interpreted within the scope of various semantic operators. These observations motivate a grammatical analysis of SIs: SIs are derived during or before semantic computation. Among various kinds of evidence for the grammati- cal approach to SIs, especially convincing one is SIs embedded in non-monotonic (NM) environments, which post-semantic analyses have difficulty deriving. This paper introduces a new example of NM operators that allow the SI-embedding in their scope, and I thereby provide further empirical support for the grammatical analysis. On the other hand, I will also show that not all NM operators behave in the same way with respect to SI-embedding. It will turn out that Strawson non- monotonicity is required to embed SIs in the negative component of NM envi- ronments; i.e. SI-embedding is unavailable if the NMity can be decomposed into monotonic assertion and monotonic presupposition.

Height-Relative Determination of (Non-Root) Modal Flavor: Evidence from Hindi

In this paper it is proposed that modal flavor is determined by the attachment height of a modal. The various interpretations of the Hindi future marker -gaa, which is taken to be a modal, are discussed. The idea put forth is that modal flavor is indirectly constrained by the semantic type of the modal’s prejacent instead of being solely determined via contextual assignment. Modal Bases are re-envisioned as being comprised of different types of alternatives (worlds, world-time pairs, etc.), rather than just sets of worlds determined by different accessibility relations. The correlation between height and attachment site falls out as a consequence of the different types of alternatives a Modal Bases make available for semantic computation.

Semantic-Driven Information Recommendation System

Information recommendation systems is the one of the most effective tools to solve the problem of information overload. In this paper, we design SIRSCA, a semantic-driven information recommendation system under cloud architecture. SIRSCA mainly includes four modules: semantics representation of foundation data and user preference informations; indexing mechanism of massive semantic informations under cloud architecture; recommendation approaches based on semantic computation theory; and technologies of dynamic migration under cloud architecture.

SCOPAS — SEMANTIC COMPUTATION OF PAGE SCORE

This paper presents a novel model for scoring web pages, entitled SCOPAS (Semantic COmputation of PAge Score). With the prolific growth in the number of users of World Wide Web and the heterogeneity of their information needs, it becomes mandatory to evaluate the relevance of a web page in terms of user specific requirements. SCOPAS is aimed at modeling the web pages to facilitate efficient evaluation by harnessing the inherent features of the page in terms of its content and structure. The proposed model further enriches the scoring procedure by fine-graining the evaluation to a micro level through segmentation of the page. A variable magnitude, multi-dimensional approach is proposed for evaluating each of the segments by incorporating the relevance of intra-segment level components. The user-interest is captured with the help of FOAF (Friend Of A Friend) Ontology to achieve personalized page scoring. The generic SCOPAS model is extended to SCOPAS-Rank, which explores utilization of the model in improving the web search engine's result ordering. A prototype implementation of the proposed SCOPAS-Rank model is developed and experiments were conducted on it. The results of the experiments validate the effectiveness of the proposed model.