PageRank is a way to rank Web pages taking into account hyper-link structure of the Web. PageRank provides efficient and simple method to find out ranking of Web pages exploiting hyper-link structure of the Web. However, it produces just an approximation of the ranking since the random surfer model uses just uniform distributions for all situation of choice happening during the surf process. In...

Attempts to profile authors based on their characteristics, including native language, have drawn attention in recent years, via several approaches using machine learning with simple features. In this paper we investigate the potential usefulness to this task of contrastive analysis from second language acquistion research, which postulates that the (syntactic) errors in a text are influenced b...

We describe BBN’s Question Answering work at TREC 2002. We focus on two issues: answer selection and confidence estimation. We found that some simple constraints on the candidate answers can improve a pure IRbased technique for answer selection. We also found that a few simple features derived from the question-answer pairs can be used for effective confidence estimation. Our results also confi...

In this document, the SURF detector-descriptor scheme used in the OpenSURF library is discussed in detail. First the algorithm is analysed from a theoretical standpoint to provide a detailed overview of how and why it works. Next the design and development choices for the implementation of the library are discussed and justified. During the implementation of the library, it was found that some ...

This work presents a study about the use of Laban Movement Analysis (LMA) as a robust tool to describe human basic behavior patterns, to be applied in human-machine interaction. LMA is a language used to describe and annotate dancing movements and is divided in components [1]: Body, Space, Shape and Effort. Despite its general framework is widely used in physical and mental therapy [2], it has ...

In this paper we report on our experiments on automatic Word Sense Disambiguation using a maximum entropy approach for both English and Chinese verbs. We compare the difficulty of the sensetagging tasks in the two languages and investigate the types of contextual features that are useful for each language. Our experimental results suggest that while richer linguistic features are useful for Eng...

A data embedding method is proposed for image authentication based on table look-up in frequency domain. A visually meaningful watermark and a set of simple features are embedded invisibly in the marked image, which can be stored in the compressed form. The scheme can detect and localize alterations of the original image, such as the tempering of images exported from a digital camera.

A model is developed and tested to explain the relationships among narcissism, privacy concern, vigilance, and exposure to risk on Facebook, with age and gender as controlling variables. Two important constructs are conceptualized and measured in this research. Facebook exposure is defined as the opportunity for privacy and security breaches on Facebook. Facebook vigilance is the extent to whic...

Supervised approaches for text summarisation suffer from the problem of mismatch between the target labels/scores of individual sentences and the evaluation score of the final summary. Reinforcement learning can solve this problem by providing a learning mechanism that uses the score of the final summary as a guide to determine the decisions made at the time of selection of each sentence. In th...

A market-based algorithm is presented which autonomously apportions complex tasks to multiple cooperating agents giving each agent the motivation of improving performance of the whole system. A speciic model, called \The Hayek Machine" is proposed and tested on a simulated Blocks World (BW) planning problem. Hayek learns to solve more complex BW problems than any previous learning algorithm. Gi...