A MACHINE LEARNING APPROACH TO TWITTER USER CLASSIFICATION PDF

THE EXPERIMENT PRESENTED IN STRUBE ET AL., 2002 IS ONE OF THE FEW DEALING WITH THE applica-tion of machine learning to German coreference resolution covering definite noun phrases, prope[r]

4 CONCLUSION TRANG 4 Figure 3: Example records corresponding to the sentence shown in Figures 1 & 2 target class: RECURSE-2 - target class: RECURSE-3 target class: GAP-3 depth: 0 depth: [r]

Multidisciplinary team (MDT) meetings are used to optimise expert decision-making about treatment options, but such expertise is not digitally transferable between centres. To help standardise medical decision-making, we developed a machine learning model designed to predict MDT decisions about adju[r]

The oxidation of protein-bound methionine to form methionine sulfoxide, has traditionally been regarded as an oxidative damage. However, recent evidences support the view of this reversible reaction as a regulatory post-translational modification.

Each time it is called, the base learning algorithm generates a new weak prediction rule, and after many rounds, the boosting algorithm must combine these weak rules into a single predic[r]

The basic idea of our approach is to build a machine learning model to automatically classify each sentence into one of the two classes, “erro-neous” and “correct.” To build the learning[r]

To further our understanding of immunopeptidomics, improved tools are needed to identify peptides presented by major histocompatibility complex class I (MHC-I). Many existing tools are limited by their reliance upon chemical affinity data, which is less biologically relevant than sampling by mass sp[r]

In this paper, we want to investigate the ad- vantage of user behaviors and re-ranking frame- work in related words retrieval task using Chi- nese input method user records. We construct a User-Word bipartite graph to represent the in- formation hiding in user r[r]

The online learning paradigm fits nicely in the IMT framework, since the interactive translation of the source sentences generates new user-validated training samples that can be used to[r]

Under the as-sumption that good machine translation will pro-duce “human-like” sentences, classifiers are trained to predict whether a sentence is authored by a human or by a machine bas[r]

Given that classification is so deeply ingrained into the way we think and communicate, it makes sense to try to write programs by classifying the different concepts inherent in a proble[r]

In this paper, we show the significant benefits adopting the Adaptive Learning Management System (ALMS) to improve the teaching quality for online courses. We set up a problem to realize and orient students in the ALMS. To solve this problem, we first show the psychological fundamentals for classify[r]

Pricing and guessing the right prices are vital for both hosts and renters on homesharing plat-form from internet based companies. To contribute the growing interest and immense literatureon applying Artificial Intelligence on predicting rental prices, this paper attempts to build ma-chine learning[r]

TWITTER MAKES IT EASY TO PUT TRANG 13 STAYING IN TOUCH twitter isn’t just about letting people know what you are about and what you’re up to; it’s also about inding other like minded peo[r]

A key theme in contemporary higher education is how assessment can be constructed so as to maximize opportunities for grownth and meaningful student learning. As each educational system measures learning through multiple and diverse assessments, including formative assessment. In addition, blended l[r]

We used a Twitter API to collect tweets that include hashtags that express sarcasm #sarcasm, #sarcastic, direct positive sentiment e.g., #happy, #joy, #lucky, and direct negative sentime[r]

Training Phase Classification Phase Machine Translation Labeled Vietnamese Unlabeled Vietnamese Labeled English Reviews Transductive SVM Sentiment Classifier Test Vietnamese Review TRANG[r]

Multi-label classification of data remains to be a challenging problem. Because of the complexity of the data, it is sometimes difficult to infer information about classes that are not mutually exclusive.

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The low success rate and high cost of drug discovery requires the development of new paradigms to identify molecules of therapeutic value. The Anatomical Therapeutic Chemical (ATC) Code System is a World Health Organization (WHO) proposed classification that assigns multi-level codes to compounds ba[r]