13 research outputs found
Enabling Operator Reordering in Data Flow Programs Through Static Code Analysis
In many massively parallel data management platforms, programs are
represented as small imperative pieces of code connected in a data flow. This
popular abstraction makes it hard to apply algebraic reordering techniques
employed by relational DBMSs and other systems that use an algebraic
programming abstraction. We present a code analysis technique based on reverse
data and control flow analysis that discovers a set of properties from user
code, which can be used to emulate algebraic optimizations in this setting.Comment: 4 pages, accepted and presented at the First International Workshop
on Cross-model Language Design and Implementation (XLDI), affiliated with
ICFP 2012, Copenhage
Discovering Mathematical Objects of Interest -- A Study of Mathematical Notations
Mathematical notation, i.e., the writing system used to communicate concepts
in mathematics, encodes valuable information for a variety of information
search and retrieval systems. Yet, mathematical notations remain mostly
unutilized by today's systems. In this paper, we present the first in-depth
study on the distributions of mathematical notation in two large scientific
corpora: the open access arXiv (2.5B mathematical objects) and the mathematical
reviewing service for pure and applied mathematics zbMATH (61M mathematical
objects). Our study lays a foundation for future research projects on
mathematical information retrieval for large scientific corpora. Further, we
demonstrate the relevance of our results to a variety of use-cases. For
example, to assist semantic extraction systems, to improve scientific search
engines, and to facilitate specialized math recommendation systems. The
contributions of our presented research are as follows: (1) we present the
first distributional analysis of mathematical formulae on arXiv and zbMATH; (2)
we retrieve relevant mathematical objects for given textual search queries
(e.g., linking with `Jacobi
polynomial'); (3) we extend zbMATH's search engine by providing relevant
mathematical formulae; and (4) we exemplify the applicability of the results by
presenting auto-completion for math inputs as the first contribution to math
recommendation systems. To expedite future research projects, we have made
available our source code and data.Comment: Proceedings of The Web Conference 2020 (WWW'20), April 20--24, 2020,
Taipei, Taiwa