It is our great pleasure to welcome you to the 2014 ACM SIGMOD/PODS Ph.D. Symposium. This year's symposium continues its tradition, which is intended to bring together Ph.D. students working on topics related to the SIGMOD and PODS conference. The workshop will offer Ph.D. students the opportunity to present, discuss, and receive feedback on their research in a constructive and international atmosphere. The workshop will be accompanied by prominent professors, researchers and practitioners in the fields of database technology. These accompanying professors will participate actively and contribute to the discussions. The call for papers attracted 13 submissions from Asia, Canada, Europe, and the United States. The program committee accepted 10 proposals that cover a variety of topics, including stream and large scale data processing, query language and query processing. In addition, the program includes a keynote speech given by Dr. Divesh Srivastava, head of the Database Research Department at AT&T Labs-Research. We hope that these proceedings will serve as a valuable reference for Ph.D. students.
Proceeding Downloads
Data stream processing in dynamic and decentralized peer-to-peer networks
Data stream management systems (DSMS) process data streams, potentially infinite amounts of data sent by active data sources. Distributed DSMS use networks of interconnected machines to enhance the processing power. Typically, clusters of equal, non-...
Efficient delegation protocols for data streams
In numerous real world applications, one needs to store almost the whole data set in order to compute certain functions of the data, where we require the answer to be exact. In my thesis, I devised a new model for data streaming algorithms where we ...
Scaling data mining in massively parallel dataflow systems
The demand for mining large datasets using shared-nothing clusters is steadily on the rise. Despite the availability of parallel processing paradigms such as MapReduce, scalable data mining is still a tough problem. Naïve ports of existing algorithms to ...
Toward unstructured mesh algebra and query language
Although several application domains use unstructured meshes as first-class citizen, there is no dedicated database system which offers querying and manipulation of such objects via a declarative query language. A declarative query language allows users ...
Persistent functional languages: toward functional relational databases
Functional languages provide new approaches to concurrency control, based on techniques such as lazy evaluation and memoization. We have designed and implemented a persistent functional language based on these ideas, which we plan to use for the ...
Data exchange for document-centric XML
Data exchange has been one of the most popular topics in the database community for the past several years. Data exchange is essential for transferring, unifying and querying heterogeneous data -- tasks which very often arise in practice. Although the ...
Data-driven recommendations for exploratory query formulation
We consider the problem of helping users explore and understand large, high dimensional structured datasets. Such users may issue queries to find data entries of interest. Given the high dimensionality and lack of detailed knowledge of the data, these ...
Query answering over ontologies specified via database dependencies
In this work we present a novel graph-based approach for studying the tractability of query answering over ontologies expressed by means of tuple-generating dependencies (TGDs). We do this by defining a new class of TGDs that subsumes all the other ...
Automated schema design for NoSQL databases
Selecting appropriate indices and materialized views is critical for high performance in relational databases. By example, we show that the problem of schema optimization is also highly relevant for NoSQL databases. We explore the problem of schema ...
SpatialHadoop: towards flexible and scalable spatial processing using mapreduce
Recently, MapReduce frameworks, e.g., Hadoop, have been used extensively in different applications that include tera-byte sorting, machine learning, and graph processing. With the huge volumes of spatial data coming from different sources, there is an ...
Index Terms
- Proceedings of the 2014 SIGMOD PhD symposium
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Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
SIGMOD'16 PhD | 10 | 9 | 90% |
SIGMOD '15 PhD Symposium | 11 | 9 | 82% |
SIGMOD'14 PhD Symposium | 13 | 10 | 77% |
SIGMOD'13 PhD Symposium | 26 | 12 | 46% |
Overall | 60 | 40 | 67% |