Social Science–guided Feature Engineering

Feature Engineering in Persian Dependency Parser

Dependency parser is one of the most important fundamental tools in the natural language processing, which extracts structure of sentences and determines the relations between words based on the dependency grammar. The dependency parser is proper for free order languages, such as Persian. In this paper, data-driven dependency parser has been developed with the help of phrase-structure parser fo...

Feature Engineering for Supervised Link Prediction on Dynamic Social Networks

Link prediction is an important network science problem in many domains such as social networks, chem/bioinformatics, etc. Most of these networks are dynamic in nature with patterns evolving over time. In such cases, it is necessary to incorporate time in the mining process in a seamless manner to aid in better prediction performance. We propose a two-step solution strategy to the link predicti...

Automating Feature Engineering

Feature Engineering is the task of transforming the feature space in a given learning problem to improve the performance of a trained model. It is a crucial but timeintensive and skillful process, involving a data scientist or a domain expert. It is often the key determinant of the time and cost required to build an effective learner. In this paper, we discuss our system for performing feature ...

Cover Feature Software Engineering

Feature Engineering for Text Classification

Most research in text classification to date has used a “bag of words” representation in which each feature corresponds to a single word. This paper examines some alternative ways to represent text based on syntactic and semantic relationships between words (phrases, synonyms and hypernyms). We describe the new representations and try to justify our hypothesis that they could improve the perfor...