Word groupings useful for language processing tasks are increasingly available, as thesauri appear online, and as distributional word clustering techniques improve. However, for many tasks, one is interested in relationships among word senses, not words. This paper presents a method for automatic sense disambiguation of nouns appearing within sets of related nouns — the kind of data one finds i...

It is well known that the length of a syntactic dependency determines its online memory cost. Thus, the problem of the placement of a head and its dependents (complements or modifiers) that minimizes online memory is equivalent to the problem of the minimum linear arrangement of a star tree. However, how that length is translated into a cognitive cost is not known. Here it is shown that the onl...

Word-of-mouth (WOM) has been recognized as one of the most influential resources of information transmission. However, conventional WOM communication is only effective within limited social contact boundaries. The advances of information technology and the emergence of online social network sites have changed the way information is transmitted and have transcended the traditional limitations of...

Multilingual speakers switch between languages in online and spoken communication. Analyses of large scale multilingual data require automatic language identification at the word level. For our experiments with multilingual online discussions, we first tag the language of individual words using language models and dictionaries. Secondly, we incorporate context to improve the performance. We ach...

Online reputation systems have been found to be an effective way to ensure honest behavior from the seller in consumer to consumer (C2C) e-commerce. At the same time, reputation systems have also been regarded as an important platform where large-scale of word-of mouth behavior and evaluations of the purchase experience could be communicated. There are altogether two components in online reputa...

This paper describes the clustering-based approach to Word Sense Disambiguation that is followed by the TKB-UO system at SemEval-2007. The underlying disambiguation method only uses WordNet as external resource, and does not use training data. Results obtained in both Coarse-grained English all-words task (task 7) and English fine-grained all-words subtask (task 17) are presented.

Word vector representation techniques, built on word-word co-occurrence statistics, often provide representations that decode the differences in meaning between various words. This significant fact is a powerful tool that can be exploited to a great deal of natural language processing tasks. In this work, we propose a simple and efficient unsupervised approach for keyphrase extraction, called R...

In this paper we propose a segmentation system for unconstrained Arabic online handwriting. An essential problem addressed by analytical-based word recognition system. The system is composed of two-stages the first is a newly special designed hidden Markov model (HMM) and the second is a rules based stage. In our system, handwritten words are broken up into characters by simultaneous segmentati...

New words are appearing everyday in online communication applications, such as Twitter1. Twitter is the world’s most famous online social networking and microblogging service that enables its users to send/read text-based messages of up to 140 characters, known as “tweets”. Due to the facts that tweets are online typed (as fast as possible) within a limited number of characters, tweets are full...