The construction of novelty in computer science papers

Novelty is a concept of great importance in the writing of a research paper, given that the author has to persuade the audience of the news value of the reported research, which makes it worth publishing. In this paper I use a corpus of computer science papers to investigate how novelty is created in this discipline. I analyse how the author uses evaluation and lexical cohesion to integrate his/her research into the existing knowledge structure of the field. Evaluation in computer science papers is closely associated with the Problem-Solution pattern which structures most of the papers: authors claim that the technology they introduce is the best solution to a problem that they have previously identified. Lexical cohesion highlights the novelty of the research by establishing a semantic relation of contrast between the fragment of text reporting previous research in the field and that reporting the authors' own research

Parallelizing Machine Learning- Functionally: A Framework and Abstractions for Parallel Graph Processing

Implementing machine learning algorithms for large data, such as the Web graph and social networks, is challenging. Even though much research has focused on making sequential algorithms more scalable, their running times continue to be prohibitively long. Meanwhile, parallelization remains a formidable challenge for this class of problems, despite frameworks like MapReduce which hide much of the associated complexity. We present a framework for implementing parallel and distributed machine learning algorithms on large graphs, flexibly, through the use of functional programming abstractions. Our aim is a system that allows researchers and practitioners to quickly and easily implement (and experiment with) their algorithms in a parallel or distributed setting. We introduce functional combinators for the flexible composition of parallel, aggregation, and sequential steps. To the best of our knowledge, our system is the first to avoid inversion of control in a (bulk) synchronous parallel model