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Advances in Data Mining. Applications and Theoretical Aspects

Overview of attention for book
Cover of 'Advances in Data Mining. Applications and Theoretical Aspects'

Table of Contents

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    Book Overview
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    Chapter 1 Risk Factors and Identifiers for Alzheimer’s Disease: A Data Mining Analysis
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    Chapter 2 Unsupervised Named Entity Recognition and Disambiguation: An Application to Old French Journals
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    Chapter 3 Multiple Template Detection Based on Segments
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    Chapter 4 Analysis and Evaluation of Web Pages Classification Techniques for Inappropriate Content Blocking
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    Chapter 5 Extending PubMed Related Article (PMRA) for Multiple Citations
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    Chapter 6 Variability of Behaviour in Electricity Load Profile Clustering; Who Does Things at the Same Time Each Day?
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    Chapter 7 Hybrid Recommender System for Prediction of the Yelp Users Preferences
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    Chapter 8 Analysis Using Popularity Awareness Index, Recency Index and Purchase Diversity in Group Buying
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    Chapter 9 Choice Modelling and Forecasting Demand for Alternative-Fuel Tractors
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    Chapter 10 Data Mining Cultural Aspects of Social Media Marketing
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    Chapter 11 A Methodology for the Diagnostic of Aircraft Engine Based on Indicators Aggregation
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    Chapter 12 Visual Trajectory Pattern Mining: An Exploratory Study in Baggage Handling Systems
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    Chapter 13 Analysis of Trajectory Data in Support of Traffic Management: A Data Mining Approach
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    Chapter 14 Detecting the Transition Stage of Cells and Cell Parts by Prototype-Based Classification
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    Chapter 15 Discovering Main Vertexical Planes in a Multivariate Data Space by Using CPL Functions
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    Chapter 16 Big Data Analytics: A Literature Review Paper
Attention for Chapter 2: Unsupervised Named Entity Recognition and Disambiguation: An Application to Old French Journals
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1 X user

Citations

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8 Dimensions

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Chapter title
Unsupervised Named Entity Recognition and Disambiguation: An Application to Old French Journals
Chapter number 2
Book title
Advances in Data Mining. Applications and Theoretical Aspects
Published in
Lecture notes in computer science, July 2014
DOI 10.1007/978-3-319-08976-8_2
Book ISBNs
978-3-31-908975-1, 978-3-31-908976-8
Authors

Yusra Mosallam, Alaa Abi-Haidar, Jean-Gabriel Ganascia

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 31%
Lecturer 2 15%
Student > Master 2 15%
Student > Bachelor 1 8%
Student > Doctoral Student 1 8%
Other 1 8%
Unknown 2 15%
Readers by discipline Count As %
Computer Science 7 54%
Business, Management and Accounting 2 15%
Arts and Humanities 1 8%
Psychology 1 8%
Unknown 2 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 November 2014.
All research outputs
#15,311,799
of 22,772,779 outputs
Outputs from Lecture notes in computer science
#4,646
of 8,123 outputs
Outputs of similar age
#131,897
of 226,904 outputs
Outputs of similar age from Lecture notes in computer science
#73
of 180 outputs
Altmetric has tracked 22,772,779 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,123 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 226,904 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 180 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.