[PDF][PDF] Spatial Crowdsourcing: Challenges and Opportunities.
As one of the successful forms of using Wisdom of Crowd, crowdsourcing, has been widely
used for many human intrinsic tasks, such as image labeling, natural language …
used for many human intrinsic tasks, such as image labeling, natural language …
Relaxed functional dependencies—a survey of approaches
L Caruccio, V Deufemia… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
Recently, there has been a renovated interest in functional dependencies due to the
possibility of employing them in several advanced database operations, such as data …
possibility of employing them in several advanced database operations, such as data …
Time series data imputation: A survey on deep learning approaches
C Fang, C Wang - arxiv preprint arxiv:2011.11347, 2020 - arxiv.org
Time series are all around in real-world applications. However, unexpected accidents for
example broken sensors or missing of the signals will cause missing values in time series …
example broken sensors or missing of the signals will cause missing values in time series …
[LIBRO][B] Real-time linked dataspaces: Enabling data ecosystems for intelligent systems
E Curry - 2020 - library.oapen.org
This open access book explores the dataspace paradigm as a best-effort approach to data
management within data ecosystems. It establishes the theoretical foundations and …
management within data ecosystems. It establishes the theoretical foundations and …
Characterizing functional dependencies in formal concept analysis with pattern structures
Computing functional dependencies from a relation is an important database topic, with
many applications in database management, reverse engineering and query optimization …
many applications in database management, reverse engineering and query optimization …
Data dependencies extended for variety and veracity: A family tree
Besides the conventional schema-oriented tasks, data dependencies are recently revisited
for data quality applications, such as violation detection, data repairing and record matching …
for data quality applications, such as violation detection, data repairing and record matching …
Sampling for big data profiling: A survey
Z Liu, A Zhang - IEEE access, 2020 - ieeexplore.ieee.org
Due to the development of internet technology and computer science, data is exploding at
an exponential rate. Big data brings us new opportunities and challenges. On the one hand …
an exponential rate. Big data brings us new opportunities and challenges. On the one hand …
Structure-aware decoupled imputation network for multivariate time series
N Ahmed, L Schmidt-Thieme - Data Mining and Knowledge Discovery, 2024 - Springer
Handling incomplete multivariate time series is an important and fundamental concern for a
variety of domains. Existing time-series imputation approaches rely on basic assumptions …
variety of domains. Existing time-series imputation approaches rely on basic assumptions …
A survey of approximate quantile computation on large-scale data
Z Chen, A Zhang - IEEE Access, 2020 - ieeexplore.ieee.org
As data volume grows extensively, data profiling helps to extract metadata of large-scale
data. However, one kind of metadata, order statistics, is difficult to be computed because …
data. However, one kind of metadata, order statistics, is difficult to be computed because …
Functional Dependencies with Predicates: What Makes the g3-error Easy to Compute?
The notion of functional dependencies (FDs) can be used by data scientists and domain
experts to confront background knowledge against data. To overcome the classical, too …
experts to confront background knowledge against data. To overcome the classical, too …