Neil Rubens | Searcharxiv

arXiv2014

Turing Test for the Internet of Things

How smart is your kettle? How smart are things in your kitchen, your house, your neighborhood, on the internet? With the advent of Internet of Things, and the move of making devices `smart' by utilizing AI, a natural question arrises, how can we evaluate the progress. The standard way of evaluating AI is through the Turing Test. While Turing Test was designed for AI; the device that it was tailored to was a computer. Applying the test to variety of devices that constitute Internet of Things poses a number of challenges which could be addressed through a number of adaptations.

cs.AI↗

arXiv2006

The Application of Fuzzy Logic to the Construction of the Ranking Function of Information Retrieval Systems

The quality of the ranking function is an important factor that determines the quality of the Information Retrieval system. Each document is assigned a score by the ranking function; the score indicates the likelihood of relevance of the document given a query. In the vector space model, the ranking function is defined by a mathematic expression. We propose a fuzzy logic (FL) approach to defining the ranking function. FL provides a convenient way of converting knowledge expressed in a natural language into fuzzy logic rules. The resulting ranking function could be easily viewed, extended, and verified: * if (tf is high) and (idf is high) > (relevance is high); * if (overlap is high) > (relevance is high). By using above FL rules, we are able to achieve performance approximately equal to the state of the art search engine Apache Lucene (deltaP10 +0.92%; deltaMAP -0.1%). The fuzzy logic approach allows combining the logic-based model with the vector model. The resulting model possesses simplicity and formalism of the logic based model, and the flexibility and performance of the vector model.

cs.IR↗