Named Entity Recognition task needs high-quality and large-scale resources. In this paper, we present RENCO, a based-rules system focused on the recognition of entities in the Cosmetic domain (brandnames, product names, ...). RENCO has two main objectives: 1) Generating resources for named entity recognition; 2) Mining new named entities relying on the previous generated resources. In order to ...

Chinese text processing requires the detection of word boundaries. This is a non-trivial step because Chinese does not contain explicit whitespace between words. Existing word segmentation techniques make use of precompiled dictionaries and treebanks. The creation of dictionaries and treebanks is a labor-intensive process and consequently they are updated infrequently. Furthermore, due to their...

In this paper, we present Singlish sentiment lexicon, a conceptlevel knowledge base for sentiment analysis that associates multiword expressions to a set of emotion labels and a polarity value. Unlike many other sentiment analysis resources, this lexicon is not built by manually labeling pieces of knowledge coming from general NLP resources such as WordNet or DBPedia. Instead, it is automatical...

with the exponential growth of social media i.e. blogs and social networks, organizations and individual persons are increasingly using the number of reviews of these media for decision making about a product or service. Opinion mining detects whether the emotions of an opinion expressed by a user on Web platforms in natural language, is positive or negative. This paper presents extensive exper...

Polarity lexicons have been a valuable resource for sentiment analysis and opinion mining. There are a number of such lexical resources available, but it is often suboptimal to use them as is, because general purpose lexical resources do not reflect domain-specific lexical usage. In this paper, we propose a novel method based on integer linear programming that can adapt an existing lexicon into...

UNLABELLED The recognition of gene/protein names in literature is one of the pivotal steps in the processing of biological literatures for information extraction or data mining. We have compiled a lexicon of biomedical words (conserved patterns/ potential motifs) which has the combination of only 20 alphabets of amino acids. The remaining 6 letters of the English alphabets (B, J, O, U, X, Z) ar...

Weblogs are a source of human activity knowledge comprising valuable information such as facts, opinions and personal experiences. In this paper, we propose a method for mining personal experiences from a large set of weblogs. We define experience as knowledge embedded in a collection of activities or events which an individual or group has actually undergone. Based on an observation that exper...

A lexicon is the heart of any language processing system. Accurate words with grammatical and semantic attributes are essential or highly desirable for any application – be it machine translation, information extraction, various forms of tagging or text mining. However, good quality lexicons are difficult to construct requiring enormous amount of time and manpower. In this paper, we present a m...

Presently, text mining in e-commerce reviews predominantly focus on singular sentiment analysis, yet constraints persist score computation, semantic inclination discernment, and lexicon construction. To address these limitations, this study establishes an user comment management system based mining. It performs part-of-speech tagging dependency grammar analysis the historical corpus of e-commer...

BACKGROUND Recently, research on human disease network has succeeded and has become an aid in figuring out the relationship between various diseases. In most disease networks, however, the relationship between diseases has been simply represented as an association. This representation results in the difficulty of identifying prior diseases and their influence on posterior diseases. In this pape...