Comparing SVM and Naive Bayes classifiers for text categorization with Wikitology as knowledge enrichment

The activity of labeling of documents according to their content is known as text categorization. Many experiments have been carried out to enhance text categorization by adding background knowledge to the document using knowledge repositories like Word Net, Open Project Directory (OPD), Wikipedia and Wikitology. In our previous work, we have carried out intensive experiments by extracting knowledge from Wikitology and evaluating the experiment on Support Vector Machine with 10- fold cross-validations. The results clearly indicate Wikitology is far better than other knowledge bases. In this paper we are comparing Support Vector Machine (SVM) and Na\"ive Bayes (NB) classifiers under text enrichment through Wikitology. We validated results with 10-fold cross validation and shown that NB gives an improvement of +28.78%, on the other hand SVM gives an improvement of +6.36% when compared with baseline results. Na\"ive Bayes classifier is better choice when external enriching is used through any external knowledge base.Comment: 5 page

The Contemporaneous Correlation of Structural Shocks and Inflation— Output Variability in Pakistan

Monetary policy has changed in a number of ways during the last two decades . Along with the other characteristics, modern monetary policy is forward-looking, and the central banks respond contemporaneously to structural shocks that are expected to make inflation deviate from the future targets. This study aims at investigating this aspect of the monetary policy for Pakistan. Using a modified version of Structural Vector Autoregression (SVAR) developed by Enders and Hurn (2007), we have found a weak response of policy to supply-side shocks as the correlation coefficient between the demand and supply shocks is only 0.041. Moreover, the results show that the demand shocks have no significant contribution to output variability. On the other hand, both the demand and supply shocks, along with the foreign supply shocks, significantly contribute to inflation variability.Monetary Policy, Contemporaneous Correlation, Pakistan, Structural Shocks, Vector Autoregression

Peak to average power ratio based spatial spectrum sensing for cognitive radio systems

The recent convergence of wireless standards for incorporation of spatial dimension in wireless systems has made spatial spectrum sensing based on Peak to Average Power Ratio (PAPR) of the received signal, a promising approach. This added dimension is principally exploited for stream multiplexing, user multiplexing and spatial diversity. Considering such a wireless environment for primary users, we propose an algorithm for spectrum sensing by secondary users which are also equipped with multiple antennas. The proposed spatial spectrum sensing algorithm is based on the PAPR of the spatially received signals. Simulation results show the improved performance once the information regarding spatial diversity of the primary users is incorporated in the proposed algorithm. Moreover, through simulations a better performance is achieved by using different diversity schemes and different parameters like sensing time and scanning interval