79,887 research outputs found
EquiX---A Search and Query Language for XML
EquiX is a search language for XML that combines the power of querying with
the simplicity of searching. Requirements for such languages are discussed and
it is shown that EquiX meets the necessary criteria. Both a graphical abstract
syntax and a formal concrete syntax are presented for EquiX queries. In
addition, the semantics is defined and an evaluation algorithm is presented.
The evaluation algorithm is polynomial under combined complexity.
EquiX combines pattern matching, quantification and logical expressions to
query both the data and meta-data of XML documents. The result of a query in
EquiX is a set of XML documents. A DTD describing the result documents is
derived automatically from the query.Comment: technical report of Hebrew University Jerusalem Israe
LexRank: Graph-based Lexical Centrality as Salience in Text Summarization
We introduce a stochastic graph-based method for computing relative
importance of textual units for Natural Language Processing. We test the
technique on the problem of Text Summarization (TS). Extractive TS relies on
the concept of sentence salience to identify the most important sentences in a
document or set of documents. Salience is typically defined in terms of the
presence of particular important words or in terms of similarity to a centroid
pseudo-sentence. We consider a new approach, LexRank, for computing sentence
importance based on the concept of eigenvector centrality in a graph
representation of sentences. In this model, a connectivity matrix based on
intra-sentence cosine similarity is used as the adjacency matrix of the graph
representation of sentences. Our system, based on LexRank ranked in first place
in more than one task in the recent DUC 2004 evaluation. In this paper we
present a detailed analysis of our approach and apply it to a larger data set
including data from earlier DUC evaluations. We discuss several methods to
compute centrality using the similarity graph. The results show that
degree-based methods (including LexRank) outperform both centroid-based methods
and other systems participating in DUC in most of the cases. Furthermore, the
LexRank with threshold method outperforms the other degree-based techniques
including continuous LexRank. We also show that our approach is quite
insensitive to the noise in the data that may result from an imperfect topical
clustering of documents
Processing Posting Lists Using OpenCL
One of the main requirements of internet search engines is the ability to retrieve relevant results with faster response times. Yioop is an open source search engine designed and developed in PHP by Dr. Chris Pollett. The goal of this project is to explore the possibilities of enhancing the performance of Yioop by substituting resource-intensive existing PHP functions with C based native PHP extensions and the parallel data processing technology OpenCL. OpenCL leverages the Graphical Processing Unit (GPU) of a computer system for performance improvements.
Some of the critical functions in search engines are resource-intensive in terms of processing power, memory, and I/O usage. The processing times vary based on the complexity and magnitude of data involved. This project involves different phases such as identifying critical resource intensive functions, initially replacing such methods with PHP Extensions, and eventually experimenting with OpenCL code. We also ran performance tests to measure the reduction in processing times. From our results, we concluded that PHP Extensions and OpenCL processing resulted in performance improvements
- …