Abstract Context: Mining Software Repositories (MSR) is a growing area of Software
Engineering (SE) research. Since their emergence in 2004, many investigations have …

Since real-world objects and their interactions are often multi-modal and multi-typed,
heterogeneous networks have been widely used as a more powerful, realistic, and generic …

Mining a set of meaningful topics organized into a hierarchy is intuitively appealing since
topic correlations are ubiquitous in massive text corpora. To account for potential …

Mining a set of meaningful and distinctive topics automatically from massive text corpora has
broad applications. Existing topic models, however, typically work in a purely unsupervised …

Large-scale multi-label text classification (LMTC) aims to associate a document with its
relevant labels from a large candidate set. Most existing LMTC approaches rely on massive …

Where can we find malware source code? This question is motivated by a real need: there is
a dearth of malware source code, which impedes various types of security research. Our …

Driven by the exponential increase of software and the advent of the pull-based
development system Git, a large amount of open-source software has emerged on various …

Instead of mining coherent topics from a given text corpus in a completely unsupervised
manner, seed-guided topic discovery methods leverage user-provided seed words to extract …

Open Source Software (OSS) is forming the spines of technology infrastructures, attracting
millions of talents to contribute. Notably, it is challenging and critical to consider both the …

Multi-label text classification refers to the problem of assigning each given document its most
relevant labels from a label set. Commonly, the metadata of the given documents and the …