70,626 research outputs found
Sustainable Building Performance and Design: a guide to finding information
Using the library to find books and journal articles on energy efiicient and sustainable buildin
A Framework for Developing Real-Time OLAP algorithm using Multi-core processing and GPU: Heterogeneous Computing
The overwhelmingly increasing amount of stored data has spurred researchers
seeking different methods in order to optimally take advantage of it which
mostly have faced a response time problem as a result of this enormous size of
data. Most of solutions have suggested materialization as a favourite solution.
However, such a solution cannot attain Real- Time answers anyhow. In this paper
we propose a framework illustrating the barriers and suggested solutions in the
way of achieving Real-Time OLAP answers that are significantly used in decision
support systems and data warehouses
siEDM: an efficient string index and search algorithm for edit distance with moves
Although several self-indexes for highly repetitive text collections exist,
developing an index and search algorithm with editing operations remains a
challenge. Edit distance with moves (EDM) is a string-to-string distance
measure that includes substring moves in addition to ordinal editing operations
to turn one string into another. Although the problem of computing EDM is
intractable, it has a wide range of potential applications, especially in
approximate string retrieval. Despite the importance of computing EDM, there
has been no efficient method for indexing and searching large text collections
based on the EDM measure. We propose the first algorithm, named string index
for edit distance with moves (siEDM), for indexing and searching strings with
EDM. The siEDM algorithm builds an index structure by leveraging the idea
behind the edit sensitive parsing (ESP), an efficient algorithm enabling
approximately computing EDM with guarantees of upper and lower bounds for the
exact EDM. siEDM efficiently prunes the space for searching query strings by
the proposed method, which enables fast query searches with the same guarantee
as ESP. We experimentally tested the ability of siEDM to index and search
strings on benchmark datasets, and we showed siEDM's efficiency.Comment: 23 page
Finding Patterns in a Knowledge Base using Keywords to Compose Table Answers
We aim to provide table answers to keyword queries against knowledge bases.
For queries referring to multiple entities, like "Washington cities population"
and "Mel Gibson movies", it is better to represent each relevant answer as a
table which aggregates a set of entities or entity-joins within the same table
scheme or pattern. In this paper, we study how to find highly relevant patterns
in a knowledge base for user-given keyword queries to compose table answers. A
knowledge base can be modeled as a directed graph called knowledge graph, where
nodes represent entities in the knowledge base and edges represent the
relationships among them. Each node/edge is labeled with type and text. A
pattern is an aggregation of subtrees which contain all keywords in the texts
and have the same structure and types on node/edges. We propose efficient
algorithms to find patterns that are relevant to the query for a class of
scoring functions. We show the hardness of the problem in theory, and propose
path-based indexes that are affordable in memory. Two query-processing
algorithms are proposed: one is fast in practice for small queries (with small
patterns as answers) by utilizing the indexes; and the other one is better in
theory, with running time linear in the sizes of indexes and answers, which can
handle large queries better. We also conduct extensive experimental study to
compare our approaches with a naive adaption of known techniques.Comment: VLDB 201
Reasoning & Querying – State of the Art
Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF
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