A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2006; you can also visit the original URL.
The file type is application/pdf.
Filters
Enterprise text processing: a sparse matrix approach
Proceedings International Conference on Information Technology: Coding and Computing
Preserved Fulltext
We demonstrate the application of sparse matrix-vector multiplication algorithms for text storage and retrieval as a means of supporting efficient and accurate text processing. ...
We demonstrate query processing using sparse matrix-vector multiplication algorithm. ...
The nature of text data in a matrix format results in a very highly sparse matrix. To save space and run time, it is important to store only the non-zero elements. ...
doi:10.1109/itcc.2001.918768
dblp:conf/itcc/GoharianGE01
fatcat:quz5nfxrlzcsnk5zx5lgnkqzve
Clustering of text documents with keyword weighting function
2019
International Journal of Intelligent Enterprise
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Documents are pre-processed and relevant keywords based on their weights are grouped together. ...
Performance of CKW is validated by clustering BBC news collection text collections. ...
Similarity measure for text processing (SMTP) for knowledge discovery considers the presence or absence of features available in the text collection. ...
doi:10.1504/ijie.2019.100029
fatcat:uytmocrskffinlouuzge6kzhka
Analysis of feature selection measures for text categorisation
2017
International Journal of Enterprise Network Management
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
The curse of dimensionality has made dimension reduction an essential step in text categorisation. Feature selection is an approach for dimension reduction. ...
Under the unsupervised approach document frequency and under the supervised approach chi-square, odds ratio, mutual information, and information gain are considered for analysis. ...
They are well suited for term-weighted matrix which is actually a sparse matrix. For the experiments conducted, libsvm3.1 by Chang and Lin (2001) is used. ...
doi:10.1504/ijenm.2017.083606
fatcat:b3z6z7fatfawnp7wjpmitbsdr4
Identification of authorship of Ukrainian-language texts of journalistic style using neural networks
2020
Eastern-European Journal of Enterprise Technologies
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
At the first stage, we convert the collection of text documents into the frequency matrix of lexemes. In the second stage, we convert the collection of text documents into a 2-dimensional matrix. ...
It is the vectorization procedure that converts input texts into the matrix, which records the frequency parameters of a lexeme [15] . ...
doi:10.15587/1729-4061.2020.195041
fatcat:wzrk4dyvvncvnfpu2a7lx2k7xe
Artificial Intelligence User Support System for SAP Enterprise Resource Planning
2017
International Joint Conference on the Analysis of Images, Social Networks and Texts
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
The system is based on an ensemble of machine learning algorithms of multiclass text classification, providing efficient question understanding, and a special framework for evidence retrieval, providing ...
A TDM is a sparse matrix, i.e. most of its elements are zeros. To prevent overfitting and ensure classes generalization and interpretability, we should remove sparse terms for each class. ...
Problem Description Enterprise resource planning (ERP) is business process management software that allows organization to use a system of integrated applications to manage the business and automate many ...
dblp:conf/aist/VlasovCRK17
fatcat:yaidgzqihnflnfr65da3sllsju
Product Quality Detection through Manufacturing Process Based on Sequential Patterns Considering Deep Semantic Learning and Process Rules
2020
Processes
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In addition, taking the data from a production enterprise in Guizhou Province as an example, the validity of the method is verified. ...
However, the production process mainly exists in the form of text. ...
Processes 2020, 8, 751 ...
doi:10.3390/pr8070751
fatcat:mqd5rej53bdfpde6ebzwl5zmym
Using Business Process Models to Retrieve Information from Governing Documents
2006
Business Information Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
In business process models the aim is to model the same domain from a process perspective. ...
In this project work we investigate the potential of utilizing text mining technologies together with a standard information retrieval systemt o link these two sources of information in a dynamic way. ...
Since process descriptions in the graphical business process models tend to be short, a direct consequence is sparse query-vectors. ...
dblp:conf/bis/LaegreidSIG06
fatcat:g5eosmg72bgkzokph4ceehwxwy
Sparse inverse kernel Gaussian Process regression
2013
Statistical analysis and data mining
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Approximate solutions for sparse Gaussian Processes have been proposed for sparse problems. ...
We propose a new technique for sparse Gaussian Process regression that allows us to compute a parsimonious model while preserving the interpretability of the sparsity structure in the data. ...
Network representing a sub-matrix of the inverse covariance matrix (b) Network representing a sub-matrix of the sparse inverse covariance matrix estimated using SPI-GP Interpretability of the model is ...
doi:10.1002/sam.11189
fatcat:sfruhls545a77erj35wijtmptm
In-storage embedded accelerator for sparse pattern processing
2016
2016 IEEE High Performance Extreme Computing Conference (HPEC)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
We present a novel architecture for sparse pattern processing, using flash storage with embedded accelerators. ...
Sparse pattern processing on large data sets is the essence of applications such as document search, natural language processing, bioinformatics, subgraph matching, machine learning, and graph processing ...
The match processing between a document-A against the whole collection can be formulated as a matrix-vector multiplication as illustrated in Figure 5 , where both the matrix and the vector are sparse. ...
doi:10.1109/hpec.2016.7761588
dblp:conf/hpec/JunNGA16
fatcat:geyok6k5lvenxnncs5bqwctr4e
An analysis of the graph processing landscape
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
The use-case of performing global computations over a graph, it is first ingested into a graph processing system from one of many digital representations. ...
Extracting information from graphs involves processing all their elements globally, and can be done with single-machine systems (with varying approaches to hardware usage), distributed systems (either ...
This system considers the adjacency matrix of the graph as a sparse matrix data structure. ...
arXiv:1911.11624v3
fatcat:t44dfa5cvfbk7exz4s2synm5z4
A Graph-Based Approach to Skill Extraction from Text
2013
Workshop on Graph-based Methods for Natural Language Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
This paper presents a system that performs skill extraction from text documents. It outputs a list of professional skills that are relevant to a given input text. ...
We make use of the texts and the hyperlink graph of Wikipedia, as well as a list of professional skills obtained from the LinkedIn social network. ...
The process decides, whether a word or a phrase or a skill suggested by a user is actually a skill through an analysis of the text contained in the user profile pages. ...
dblp:conf/textgraphs/KivimakiPDVFBS13
fatcat:hsybvsjflbf4tgg43vi6nyt4u4
An Embedding Model for Predicting Roll-Call Votes
2016
Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
We develop a novel embedding-based model for predicting legislative roll-call votes from bill text. ...
These vectors are learned to correspond with pre-trained word embeddings which allows us to analyze which features in a bill text are most predictive of political support. ...
To create our dataset, we first find a list of all votes on the full text of bills, and create a matrix of how each congressperson voted on each bill, which will be used in training and in testing. ...
doi:10.18653/v1/d16-1221
dblp:conf/emnlp/KraftJR16
fatcat:fsklp4grpfgatoy6fheyyse74m
Web Query Processing Approaches A Survey and Comparison
2014
International Journal of Computer Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
In this survey we are discussing on each of these topics and including how synonyms adding approach and Linguistic based approach are used in web query processing. ...
The web search is enabled by navigating hyperlinks in a webpage or through search engines or by web programming. ...
The first step is to use the text to construct a matrix X, in which the row vectors represent words and the column vectors represent chunks of text (e.g., sentences, paragraphs, documents). ...
doi:10.5120/14893-3362
fatcat:qlux6724hfgpnof2k43dqrc5gq
Research on professional talent training technology based on multimedia remote image analysis
2019
EURASIP Journal on Image and Video Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Based on this, this study analyzes the facial expression image and uses the wavelet transform algorithm to process the face image in complex lighting environment, thus improving the online transmission ...
The experimental results show that the proposed method has a significant improvement in the correct rate compared with the traditional LBP feature classification method and can improve the theoretical ...
Thereafter, the wavelet transform is used to process I^′ to obtain a low-frequency face image matrix LL i and a high-frequency face image matrix HL i , LH i , and HH i . ...
doi:10.1186/s13640-019-0437-4
fatcat:izr2cdzxtvddxazlv3cxruhg7a
Evolving Signal Processing for Brain–Computer Interfaces
2012
Proceedings of the IEEE
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Here we discuss the current neuroscientific questions and data processing challenges facing BCI designers and outline some promising current and future directions to address them. ...
| Because of the increasing portability and wearability of noninvasive electrophysiological systems that record and process electrical signals from the human brain, automated systems for assessing changes ...
When applied to suitable data, sparse signal processing and modeling approaches can achieve dramatically better statistical power than methods that ignore sparsity, particularly when applied to sparse ...
doi:10.1109/jproc.2012.2185009
fatcat:ebed3ribeneptnatoxaoyzn4xm
« Previous
Showing results 1 — 15 out of 6,409 results