We explore the effects of individualand network-level negative word-of-mouth on the firm’s profits using an agent-based model and specifically, an extended small world analysis. We include both permanent strong ties within the social network, and changing, often random, weak ties with other networks. The effect of negative word-of-mouth on the Net Present Value (NPV) of the firm was found to be...

Daar bestaan heelwat verwarring oor die kriteria wat op professionele status toegepas word sow el as oor die korrekte gebruik van die woord “ professie” o f “ beroep” . Dit het onsekerheid by verpleegsters veroorsaak waarvoor daar sow el in Suid-A frika as in ander lande geen grond bestaan nie. Yerpleging word alte dikwels volgens die tradisionele beeld van vroeére professioneles b eoord eel va...

Selecting the most appropriate sense for an ambiguous word in a sentence is a central problem in Natural Language Processing. In this paper, we present a method that attempts to disambiguate all the nouns, verbs, adverbs and adjectives in a text, using the senses provided in WordNet. The senses are ranked using two sources of information: (1) the Inter-net for gathering statistics for word-word...

The Inversion Algorithm is an event driven algorithm whose performance meets or exceeds that of traditional compiled-code simulators. However, existing implementations of the algorithm do not allow several vectors to be packed into a single word, thus limiting the power of the algorithm. Because the Inversion Algorithm does not represent net values in the conventional way, the simple packing te...

Optimal ensembling (OE) is a word sense disambiguation (WSD) method using word-specific training factors (average positive vs negative training per sense, posex and negex) to predict best system (classifier algorithm / applicable feature set) for given target word. Our official entry (OE1) in Senseval-4 Task 17 (coarse-grained English lexical sample task) contained many design flaws and thus fa...

This paper describes phone modelling improvements t o the hybrid ronnectionist-hidden Markov model speech recognition system developed a t Cambridge University. These improvements are applied to phone recognition from the TIMIT task and word recognition from the Wall Street Journal (WSJ) task. A recurrent net is used to map acoustic vectors t o posterior probabilities of phone classes. The maxi...

Annotating words in a historical document image archive for word recognition purpose demands time and skilled human resource (like historians, paleographers). In real-life scenario, obtaining sample images all possible is also not feasible. However, zero-shot learning methods could aptly be used to recognize unseen/out-of-lexicon such images. Based on previous state-of-the-art method “Pho(SC)Ne...

conclusions the findings of this study indicate that the frequency of disfluencies was increased in difficult syllable structures in comparison to simple syllable structures. according to the results, it seems that certain linguistic features, such as syllable structure can affect speech-motor output in people who stutter through affecting phonological encoding. background stuttering is one of ...

In this article, we introduce a new task, visual sense disambiguation for verbs: given an image and a verb, assign the correct sense of the verb, i.e., the one that describes the action depicted in the image. Just as textual word sense disambiguation is useful for a wide range of NLP tasks, visual sense disambiguation can be useful for multimodal tasks such as image retrieval, image description...