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14 Result(s)
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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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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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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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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...
