7,359 research outputs found
Logic Programming Applications: What Are the Abstractions and Implementations?
This article presents an overview of applications of logic programming,
classifying them based on the abstractions and implementations of logic
languages that support the applications. The three key abstractions are join,
recursion, and constraint. Their essential implementations are for-loops, fixed
points, and backtracking, respectively. The corresponding kinds of applications
are database queries, inductive analysis, and combinatorial search,
respectively. We also discuss language extensions and programming paradigms,
summarize example application problems by application areas, and touch on
example systems that support variants of the abstractions with different
implementations
Explainable Patterns: Going from Findings to Insights to Support Data Analytics Democratization
In the past decades, massive efforts involving companies, non-profit
organizations, governments, and others have been put into supporting the
concept of data democratization, promoting initiatives to educate people to
confront information with data. Although this represents one of the most
critical advances in our free world, access to data without concrete facts to
check or the lack of an expert to help on understanding the existing patterns
hampers its intrinsic value and lessens its democratization. So the benefits of
giving full access to data will only be impactful if we go a step further and
support the Data Analytics Democratization, assisting users in transforming
findings into insights without the need of domain experts to promote
unconstrained access to data interpretation and verification. In this paper, we
present Explainable Patterns (ExPatt), a new framework to support lay users in
exploring and creating data storytellings, automatically generating plausible
explanations for observed or selected findings using an external (textual)
source of information, avoiding or reducing the need for domain experts. ExPatt
applicability is confirmed via different use-cases involving world demographics
indicators and Wikipedia as an external source of explanations, showing how it
can be used in practice towards the data analytics democratization.Comment: 8 Figures, 10 pages, submitted to VIS 202
Explaining Queries over Web Tables to Non-Experts
Designing a reliable natural language (NL) interface for querying tables has
been a longtime goal of researchers in both the data management and natural
language processing (NLP) communities. Such an interface receives as input an
NL question, translates it into a formal query, executes the query and returns
the results. Errors in the translation process are not uncommon, and users
typically struggle to understand whether their query has been mapped correctly.
We address this problem by explaining the obtained formal queries to non-expert
users. Two methods for query explanations are presented: the first translates
queries into NL, while the second method provides a graphic representation of
the query cell-based provenance (in its execution on a given table). Our
solution augments a state-of-the-art NL interface over web tables, enhancing it
in both its training and deployment phase. Experiments, including a user study
conducted on Amazon Mechanical Turk, show our solution to improve both the
correctness and reliability of an NL interface.Comment: Short paper version to appear in ICDE 201
Answering Count Questions with Structured Answers from Text
In this work we address the challenging case of answering count queries in web search, such as ``number of songs by John Lennon''. Prior methods merely answer these with a single, and sometimes puzzling number or return a ranked list of text snippets with different numbers. This paper proposes a methodology for answering count queries with inference, contextualization and explanatory evidence. Unlike previous systems, our method infers final answers from multiple observations, supports semantic qualifiers for the counts, and provides evidence by enumerating representative instances. Experiments with a wide variety of queries, including existing benchmark show the benefits of our method, and the influence of specific parameter settings. Our code, data and an interactive system demonstration are publicly available at https://github.com/ghoshs/CoQEx and https://nlcounqer.mpi-inf.mpg.de/
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