We take an algorithmic and computational approach to the problem of providing patent recommendations, developing a web interface that allows users to upload their draft patent and returns a list of ranked relevant patents in real time. We develop scalable, distributed algorithms based on optimization techniques and sparse machine learning, with a focus on both accuracy and speed.

The following paper presents a lexical analysis component as implemented in the PANACEA project. The goal is to automatically extract lexicon entries from crawled corpora, in an attempt to use corpus-based methods for high-quality linguistic text processing, and to focus on the quality of data without neglecting quantitative aspects. Lexical analysis has the task to assign linguistic informatio...

In this paper we present an architecture for large scale DNS monitoring. The analysis of DNS traffic is becoming of first importance currently, as it allows to monitor the main part of the interactions on the Internet. DNS traffic can reveal anomalies such as worm infected hosts, botnets or spam participating hosts. The efficiency and the speed of detection of such anomalies rely on the capacit...

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Guttman scale analysis may be considered as two inseparable endeavors: (1) to ascertain if a set of stimu!'i are unidimensional in nature and if so, (2) to tank order respondents along the same continuum based on their reaction to toe stimuli. For example, suppose a set of four attitude statements (S1-54) are constructed such that similarity of content exists (e.g. all concern attitude toward i...

In this paper we propose a technique for classifying images by modeling features extracted at di erent scales. Speci cally, we use texture measures derived from Pap smear cell nuclei images using a Grey Level Co-occurrence Matrix (GLCM). For a texture feature extracted from the GLCM at a number of distances we hypothesise that by modeling the feature as a continuous function of scale we can obt...

introduction: the present study aimed to investigate the psychometric properties of grasha-riechmann student learning styles scale. method: the participants included 1039 students (421 students in human and 618 students in technical sciences), selected through the stratified sampling method from tehran university. they answered the grasha-riechmann student learning style scale and the data was ...

This paper presents a nonparametric region competition algorithm which combines scale-space clustering and region competition to segment the image. It also proposes a formal and general procedure to automatically find the initial regions. Our algorithm can also segment an image into regions which are not homogeneous in the sense of statistics, but is homogeneous in the sense of semantics with r...

This paper introduces a new generalisation of the familiar scale-space and wavelet representations, designed specifically to deal with the complexities of representing motions induced in an image sequence by the movement of 3-D objects of which the scene is comprised. It does this by combining an affine representation of local image motions with a local structure model based on Gaussian functio...

Spatial structure in ecological communities is increasingly recognized as being important for the understanding of the processes driving communities. In ecological communities, spatial patterns are either driven by environmental factors or biotic processes. Thus to adequately understand ecological communities it is important to identify the spatial structures and then relate these patterns to u...