This paper presents a machine learning approach for identification of Bengali multiword expressions (MWE) which are bigram nominal compounds. Our proposed approach has two steps: (1) candidate extraction using chunk information and various heuristic rules and (2) training the machine learning algorithm called Random Forest to classify the candidates into two groups: bigram nominal compound MWE ...

The identification of homologies between protein sequences is a central problem in molecular biology and several algorithms have been proposed for accomplishing this task. The Needleman-Wunsch Algorithm and its close variant, the SmithWaterman dynamic programming methods, solve the problem exactly in quadratic time and space. However, due to the massive amount of data involved in sequence-to-da...

The identification and selection of adequate input variables and lag structures without domain knowledge represents one the core challenges in modeling neural networks for time series prediction. Although a number of linear methods have been established in statistics and engineering, they provide limited insights for nonlinear patterns and time series without equidistant observations and shifti...

The paper transfers previous insights on coping with unconsidered context of formalized knowledge to the field of Machine Learning by translating the two main steps of coping with unconsidered contexts, namely context identification and context classification. For identification, two alternative heuristic methods are suggested. For classification the use of standard Machine Learning methods on ...

A character-based measure of similarity is an important component of many natural language processing systems, including approaches to transliteration, coreference, word alignment, spelling correction, and the identification of cognates in related vocabularies. We propose an alignment-based discriminative framework for string similarity. We gather features from substring pairs consistent with a...

Sentiment mining is a computational approach used to identify expressions made about topics within a span of text. The blogosphere is a particularly useful corpus for sentiment mining because bloggers express a wide variety of opinions and sentiments in their online journals. Previous works on sentiment identification and extraction have been primarily focused on using machine-learning methods ...

The OPT submission to the Shared Task of the 2016 Conference on Natural Language Learning (CoNLL) implements a ‘classic’ pipeline architecture, combining binary classification of (candidate) explicit connectives, heuristic rules for non-explicit discourse relations, ranking and ‘editing’ of syntactic constituents for argument identification, and an ensemble of classifiers to assign discourse se...

This paper presents a rapid software prototyping environment, based on Matlab/Simulink, for realtime simulation and control of a mini-helicopter robot. The application of the environment is illustrated with a software-in-the-loop simulation example. The environment is integrated by own modules (mini-helicopter simulation model, navigation filter, multirate control, filters) and modules based on...

Gatekeeping theories have been a popular heuristic for describing information control for years, but none have attained a full theoretical status in the context of networks. This article aims to propose a theory of network gatekeeping comprised of two components: identification and salience. Network gatekeeping identification lays out vocabulary and naming foundations through the identification...

Gatekeeping theories have been a popular heuristic for describing information control for years, but none have attained a full theoretical status in the context of networks. This paper aims to propose a theory of Network Gatekeeping comprised of two components: Identification and Salience. Network Gatekeeping Identification lays out vocabulary and naming foundations through the identification o...