2,947 research outputs found
Distributed Subweb Specifications for Traversing the Web
Link Traversal-based Query Processing (ltqp), in which a sparql query is
evaluated over a web of documents rather than a single dataset, is often seen
as a theoretically interesting yet impractical technique. However, in a time
where the hypercentralization of data has increasingly come under scrutiny, a
decentralized Web of Data with a simple document-based interface is appealing,
as it enables data publishers to control their data and access rights. While
ltqp allows evaluating complex queries over such webs, it suffers from
performance issues (due to the high number of documents containing data) as
well as information quality concerns (due to the many sources providing such
documents). In existing ltqp approaches, the burden of finding sources to query
is entirely in the hands of the data consumer. In this paper, we argue that to
solve these issues, data publishers should also be able to suggest sources of
interest and guide the data consumer towards relevant and trustworthy data. We
introduce a theoretical framework that enables such guided link traversal and
study its properties. We illustrate with a theoretic example that this can
improve query results and reduce the number of network requests. We evaluate
our proposal experimentally on a virtual linked web with specifications and
indeed observe that not just the data quality but also the efficiency of
querying improves.
Under consideration in Theory and Practice of Logic Programming (TPLP).Comment: Under consideration in Theory and Practice of Logic Programming
(TPLP
Any-k: Anytime Top-k Tree Pattern Retrieval in Labeled Graphs
Many problems in areas as diverse as recommendation systems, social network
analysis, semantic search, and distributed root cause analysis can be modeled
as pattern search on labeled graphs (also called "heterogeneous information
networks" or HINs). Given a large graph and a query pattern with node and edge
label constraints, a fundamental challenge is to nd the top-k matches ac-
cording to a ranking function over edge and node weights. For users, it is di
cult to select value k . We therefore propose the novel notion of an any-k
ranking algorithm: for a given time budget, re- turn as many of the top-ranked
results as possible. Then, given additional time, produce the next lower-ranked
results quickly as well. It can be stopped anytime, but may have to continues
until all results are returned. This paper focuses on acyclic patterns over
arbitrary labeled graphs. We are interested in practical algorithms that
effectively exploit (1) properties of heterogeneous networks, in particular
selective constraints on labels, and (2) that the users often explore only a
fraction of the top-ranked results. Our solution, KARPET, carefully integrates
aggressive pruning that leverages the acyclic nature of the query, and
incremental guided search. It enables us to prove strong non-trivial time and
space guarantees, which is generally considered very hard for this type of
graph search problem. Through experimental studies we show that KARPET achieves
running times in the order of milliseconds for tree patterns on large networks
with millions of nodes and edges.Comment: To appear in WWW 201
The Best Trail Algorithm for Assisted Navigation of Web Sites
We present an algorithm called the Best Trail Algorithm, which helps solve
the hypertext navigation problem by automating the construction of memex-like
trails through the corpus. The algorithm performs a probabilistic best-first
expansion of a set of navigation trees to find relevant and compact trails. We
describe the implementation of the algorithm, scoring methods for trails,
filtering algorithms and a new metric called \emph{potential gain} which
measures the potential of a page for future navigation opportunities.Comment: 11 pages, 11 figure
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