19,531 research outputs found
Exploring Communities in Large Profiled Graphs
Given a graph and a vertex , the community search (CS) problem
aims to efficiently find a subgraph of whose vertices are closely related
to . Communities are prevalent in social and biological networks, and can be
used in product advertisement and social event recommendation. In this paper,
we study profiled community search (PCS), where CS is performed on a profiled
graph. This is a graph in which each vertex has labels arranged in a
hierarchical manner. Extensive experiments show that PCS can identify
communities with themes that are common to their vertices, and is more
effective than existing CS approaches. As a naive solution for PCS is highly
expensive, we have also developed a tree index, which facilitate efficient and
online solutions for PCS
Discourse Structure in Machine Translation Evaluation
In this article, we explore the potential of using sentence-level discourse
structure for machine translation evaluation. We first design discourse-aware
similarity measures, which use all-subtree kernels to compare discourse parse
trees in accordance with the Rhetorical Structure Theory (RST). Then, we show
that a simple linear combination with these measures can help improve various
existing machine translation evaluation metrics regarding correlation with
human judgments both at the segment- and at the system-level. This suggests
that discourse information is complementary to the information used by many of
the existing evaluation metrics, and thus it could be taken into account when
developing richer evaluation metrics, such as the WMT-14 winning combined
metric DiscoTKparty. We also provide a detailed analysis of the relevance of
various discourse elements and relations from the RST parse trees for machine
translation evaluation. In particular we show that: (i) all aspects of the RST
tree are relevant, (ii) nuclearity is more useful than relation type, and (iii)
the similarity of the translation RST tree to the reference tree is positively
correlated with translation quality.Comment: machine translation, machine translation evaluation, discourse
analysis. Computational Linguistics, 201
A Review of the Energy Efficient and Secure Multicast Routing Protocols for Mobile Ad hoc Networks
This paper presents a thorough survey of recent work addressing energy
efficient multicast routing protocols and secure multicast routing protocols in
Mobile Ad hoc Networks (MANETs). There are so many issues and solutions which
witness the need of energy management and security in ad hoc wireless networks.
The objective of a multicast routing protocol for MANETs is to support the
propagation of data from a sender to all the receivers of a multicast group
while trying to use the available bandwidth efficiently in the presence of
frequent topology changes. Multicasting can improve the efficiency of the
wireless link when sending multiple copies of messages by exploiting the
inherent broadcast property of wireless transmission. Secure multicast routing
plays a significant role in MANETs. However, offering energy efficient and
secure multicast routing is a difficult and challenging task. In recent years,
various multicast routing protocols have been proposed for MANETs. These
protocols have distinguishing features and use different mechanismsComment: 15 page
Augmenting the 6-3-5 method with design information
This paper describes a comparative study between the 6-3-5 Method and the ICR Grid. The ICR Grid is an evolved variant of 6-3-5 intended to better integrate information into the concept generation process. Unlike a conventional 6-3-5 process where participants continually sketch concepts, using the ICR Grid (the name derived from its Inform, Create, Reflect activities and structured, grid-like output) participants are additionally required to undertake information search tasks, use specific information items for concept development, and reflect on the merit of concepts as the session progresses. The results indicate that although the quantity of concepts was lower, the use of information had a positive effect in a number of areas, principally the quality and variety of output. Although grounded in the area of product development, this research is applicable to any organisation undertaking idea generation and problem solving. As well as providing insights on the transference of information to concepts, it holds additional interest for studies on the composition and use of digital libraries
Forecasting the cost of processing multi-join queries via hashing for main-memory databases (Extended version)
Database management systems (DBMSs) carefully optimize complex multi-join
queries to avoid expensive disk I/O. As servers today feature tens or hundreds
of gigabytes of RAM, a significant fraction of many analytic databases becomes
memory-resident. Even after careful tuning for an in-memory environment, a
linear disk I/O model such as the one implemented in PostgreSQL may make query
response time predictions that are up to 2X slower than the optimal multi-join
query plan over memory-resident data. This paper introduces a memory I/O cost
model to identify good evaluation strategies for complex query plans with
multiple hash-based equi-joins over memory-resident data. The proposed cost
model is carefully validated for accuracy using three different systems,
including an Amazon EC2 instance, to control for hardware-specific differences.
Prior work in parallel query evaluation has advocated right-deep and bushy
trees for multi-join queries due to their greater parallelization and
pipelining potential. A surprising finding is that the conventional wisdom from
shared-nothing disk-based systems does not directly apply to the modern
shared-everything memory hierarchy. As corroborated by our model, the
performance gap between the optimal left-deep and right-deep query plan can
grow to about 10X as the number of joins in the query increases.Comment: 15 pages, 8 figures, extended version of the paper to appear in
SoCC'1
- …