@article{behm2011asterix,
  abstract = {ASTERIX is a new data-intensive storage and computing platform project spanning UC Irvine, UC Riverside, and UC San Diego. In this paper we provide an overview of the ASTERIX project, starting with its main goal—the storage and analysis of data pertaining to evolving-world models . We describe the requirements and associated challenges, and explain how the project is addressing them. We provide a technical overview of ASTERIX, covering its architecture, its user model for data and queries, and its approach to scalable query processing and data management. ASTERIX utilizes a new scalable runtime computational platform called Hyracks that is also discussed at an overview level; we have recently made Hyracks available in open source for use by other interested parties. We also relate our work on ASTERIX to the current state of the art and describe the research challenges that we are currently tackling as well as those that lie ahead.},
  address = {Netherlands},
  affiliation = {University of California, Irvine, USA},
  author = {Behm, Alexander and Borkar, Vinayak and Carey, Michael and Grover, Raman and Li, Chen and Onose, Nicola and Vernica, Rares and Deutsch, Alin and Papakonstantinou, Yannis and Tsotras, Vassilis},
  doi = {10.1007/s10619-011-7082-y},
  interhash = {3e06363406f716c5d9340dc2c693adb3},
  intrahash = {42d96cc4877943527a9259424c584740},
  issn = {0926-8782},
  journal = {Distributed and Parallel Databases},
  keyword = {Computer Science},
  number = 3,
  pages = {185--216},
  publisher = {Springer},
  title = {ASTERIX: towards a scalable, semistructured data platform for evolving-world models},
  url = {http://dx.doi.org/10.1007/s10619-011-7082-y},
  volume = 29,
  year = 2011
}

@inproceedings{balmin2004objectrank,
  abstract = {The ObjectRank system applies authority-based ranking to keyword search in databases modeled as labeled graphs. Conceptually, authority originates at the nodes (objects) containing the keywords and flows to objects according to their semantic connections. Each node is ranked according to its authority with respect to the particular keywords. One can adjust the weight of global importance, the weight of each keyword of the query, the importance of a result actually containing the keywords versus being referenced by nodes containing them, and the volume of authority flow via each type of semantic connection. Novel performance challenges and opportunities are addressed. First, schemas impose constraints on the graph, which are exploited for performance purposes. Second, in order to address the issue of authority ranking with respect to the given keywords (as opposed to Google's global PageRank) we precompute single keyword ObjectRanks and combine them during run time. We conducted user surveys and a set of performance experiments on multiple real and synthetic datasets, to assess the semantic meaningfulness and performance of ObjectRank.},
  author = {Balmin, Andrey and Hristidis, Vagelis and Papakonstantinou, Yannis},
  booktitle = {VLDB '04: Proceedings of the Thirtieth international conference on Very large data bases},
  interhash = {efd9340c271ab9a06e838e2f41bb7197},
  intrahash = {205f3b36bce9a060512e1c6187a30f24},
  isbn = {0-12-088469-0},
  location = {Toronto, Canada},
  pages = {564--575},
  publisher = {VLDB Endowment},
  title = {Objectrank: authority-based keyword search in databases},
  url = {http://portal.acm.org/citation.cfm?id=1316739},
  year = 2004
}