This paper presents our work on textual inference and situates it within the context of the larger goals of machine reading. The textual inference task is to determine if the meaning of one text can be inferred from the meaning of another combined with background knowledge. Most existing work either provides only very limited text understanding by using bag-of-words lexical similarity models or...

This paper describes our participation at the ImageClef 2009 medical annotation task. In this task we have used the bag-of-words approach for image representation. We submitted one run, using support-vector-machines trained on the visual word histograms in multiple scales. In this task our result ranked first, with error score of 852.8.

This paper describes our participation in Genre Tagging Task of MediaEval 2011, which aims to predict the videos’ category label. We use bag-of-words approaches with different features derived from visual content and associated textual information. We perform different experiments in which different constellations in respect of single modalities, classification methods, visual features and thei...

a time-domain approach is presented to calculate electromagnetic fields inside a large electromagnetic pulse (emp) simulator. this type of emp simulator is used for studying the effect of electromagnetic pulses on electrical apparatus in various structures such as vehicles, a reoplanes, etc. the simulator consists of three planar transmission lines. to solve the problem, we first model the meta...

This paper introduces a novel language model (LM) adaptation method based on mixture of latent word language models (LWLMs). LMs are often constructed as mixture of n-gram models, whose mixture weights are optimized using target domain data. However, n-gram mixture modeling is not flexible enough for domain adaptation because model merger is conducted on the observed word space. Since the words...

Automatic facial expression recognition (AFER) has undergone substantial advancement over the past two decades. This work explores the application of bag of words (BoW), a highly matured approach for object and scene recognition to AFER. We proceed by first highlighting the reasons that makes the task for BoW differ for AFER compared to object and scene recognition. We propose suitable extensio...