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Chapter
Introduction
In recent years, with the development of the information age, the amount of data has grown dramatically. At the same time, dirty data have already existed in various types of databases. Due to the negative imp...
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Chapter
Dirty Data Impacts on Regression Models
Due to the negative influence of dirty data on the accuracy of regression models, the relation between the data quality and model results is able to be used in the selection of proper regression models and dir...
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Chapter and Conference Paper
Effects of Properties of Montmorillonite on the Formation of Oil-Mineral Aggregates
Spilled oil can collide with suspended minerals in the water column to form oil-mineral aggregates (OMA) under the wave action, which can bring a threat to the marine environment and life. In this paper, the e...
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Book
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Chapter and Conference Paper
ANSWER: Automatic Index Selector for Knowledge Graphs
Efficient access to knowledge graphs is identified as the basic premise to make full use of knowledge graphs. Since the query processing efficiency is mainly affected by index configuration, it is necessary to...
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Chapter
Density-Based Clustering for Incomplete Data
In real world, missing values exist in a lot of data sets and cause data incompleteness. However, traditional missing value imputation methods are not suitable for density-based clustering and affect the accur...
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Chapter
Cost-Sensitive Decision Tree Induction on Dirty Data
As the rapid growth of data in our society, dirty data are increasingly common. In the process of cost-sensitive decision tree induction, dirty data in training data sets have negative impacts on the selection...
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Chapter
Impacts of Dirty Data on Classification and Clustering Models
Since dirty data have negative influence on the accuracy of machine learning models, the relation between data quality and model results could be used in the selection of the proper model and data cleaning str...
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Chapter
Incomplete Data Classification with View-Based Decision Tree
Missing values bring negative influence in data analyses and decrease the accuracy of machine learning models. Since traditional classification methods are only able to be adopted on complete data sets, this c...
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Chapter
Feature Selection on Inconsistent Data
With the explosive growth of data size, inconsistent data appear more frequently. Due to inconsistent data detection and repairing in data preprocessing, feature selection approaches are lack of efficiency. To...
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Chapter and Conference Paper
Multi-SQL: An Automatic Multi-model Data Management System
Nowadays, data in applications become diverse and large in scale. In order to meet the increasing demand for multi-model data management, multi-model databases have evolved into huge systems with many knobs. H...
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Article
PreKar: A learned performance predictor for knowledge graph stores
Effective knowledge graph storage management is identified as the basic premise to make full use of knowledge graphs. Due to the lack of performance evaluation for knowledge graph stores, it is difficult for u...
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Article
Effects of chemical dispersant on the surface properties of kaolin and aggregation with spilled oil
After oil spills occur, dispersed oil droplets can collide with suspended particles in the water column to form the oil-mineral aggregate (OMA) and settle to the seafloor. However, only a few studies have conc...
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Chapter and Conference Paper
Dirty-Data Impacts on Regression Models: An Experimental Evaluation
Data quality issues have attracted widespread attentions due to the negative impacts of dirty data on regression model results. The relationship between data quality and the accuracy of results could be applie...
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Article
TAILOR: time-aware facility location recommendation based on massive trajectories
In traditional facility location recommendations, the objective is to select the best locations which maximize the coverage or convenience of users. However, since users’ behavioral habits are often influenced...
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Chapter and Conference Paper
State Spatial Selectivity and Its Impacts on Urban Sprawl: Insights from Remote Sensing Images of Zhuhai
This research unfolds a fuller picture of how state spatial selectivity (SSS) impacts Chinese urban growth through a case study of Zhuhai. Processing remote date image, three stages of Zhuhai’s urban sprawl we...
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Article
A survey of query result diversification
Nowadays, in information systems such as web search engines and databases, diversity is becoming increasingly essential and getting more and more attention for improving users’ satisfaction. In this sense, que...
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Chapter and Conference Paper
Capture Missing Values with Inference on Knowledge Base
Data imputation is a basic step for data cleaning. Traditional data imputation approaches are lack of accuracy in the absence of knowledge. Involving knowledge base in imputation could overcome this shortcomin...
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Chapter
Short-Interval Monitoring of Land Use and Land Cover Change Using a Time Series of RADARSAT-2 Polarimetric SAR Images
There are many illegal land use sites in develo** countries that are experiencing a process of rapid urbanization. Short-interval, such as monthly, land use and land cover (LULC) change information is import...
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Chapter
Integrating Change Vector Analysis, Post-Classification Comparison, and Object-Oriented Image Analysis for Land Use and Land Cover Change Detection Using RADARSAT-2 Polarimetric SAR Images
This study proposes a new method for land use and land cover (LULC) change detection using RADARSAT-2 polarimetric SAR (PolSAR) images. The proposed method combines change vector analysis (CVA) and post-classi...
