Rating a page to be a best one, based only on Page Ranking algorithm of Brin and Page would be insufficient. This method relied totally on Link information alone. However, due to application of Soft Computing in Data Mining and Knowledge Discovery, machines were made more effective, additional features of a Page involving its indexing, terms used, capitalizations, anchor texts, hit information,...

Directly conditioned fear and avoidance readily generalises to dissimilar but conceptually related stimuli. Here, for the first time, we examined the conceptual/semantic generalisation of both fear and avoidance using real words (synonyms). Participants were first exposed to a differential fear conditioning procedure in which one word (e.g., "broth"; CS+) was followed with brief electric shock ...

Concept mapping is vital to natural language processing (NLP) for bioinformatics. Query expansion using synonyms for subterm substitutions is an effective technique to increase recall when no direct concept mapping can be found through normalization. For example, no concept can be found by direct mapping through normalization if the source vocabulary is “calcaneal fracture”. By substituting the...

MOTIVATION Genes and proteins are often associated with multiple names. More names are added as new functional or structural information is discovered. Because authors can use any one of the known names for a gene or protein, information retrieval and extraction would benefit from identifying the gene and protein terms that are synonyms of the same substance. RESULTS We have explored four com...

It is shown that basic language processes such as the production of free word associations and the generation of synonyms can be simulated using statistical models that analyze the distribution of words in large text corpora. According to the law of association by contiguity, the acquisition of word associations can be explained by Hebbian learning. The free word associations as produced by sub...

Distributional measures of semantic relatedness determine word similarity based on how frequently a pair of words appear in the same contexts. A typical method is to construct a word-context matrix, then re-weight it using some measure of association, and finally take the vector distance as a measure of similarity. This has largely been an unsupervised process, but in recent years more work has...

We propose a new method for translation acquisition which uses a set of synonyms to acquire translations from comparable corpora. The motivation is that, given a certain query term, it is often possible for a user to specify one or more synonyms. Using the resulting set of query terms has the advantage that we can overcome the problem that a single query term’s context vector does not always re...

Plesionyms, or near-synonyms, are words that are almost synonyms, but not quite. The need to deal adequately with plesionymy in tasks such as lexical choice is the basis for two alternatives to conventional models of lexical knowledge: a Saussurean approach and a prototype-theory approach. In this paper, I will discuss these approaches, showing that the latter is troublesome but the former is l...

Computing the semantic similarity between terms relies on existence and usage of semantic resources. However, these resources, often composed of equivalent units, or synonyms, must be first analyzed and weighted in order to define within them the reliability zones where the semantic cohesiveness is stronger. We propose an original method for acquisition of elementary synonyms based on exploitat...

Turney (2001) has shown that computing the mutual information of a pair of words by using cooccurrence counts obtained via queries to the AltaVista search engine performs very effectively in a synonym detection task. Since manual synonym detection is a challenging task for terminologists, we investigate whether the AltaVista-based Mutual Information (AVMI) method can be applied to the task of f...