@article{chen2009interaction,
  abstract = {A critiquing-based recommender system acts like an artificial salesperson. It engages users in a conversational dialog where users can provide feedback in the form of critiques to the sample items that were shown to them. The feedback, in turn, enables the system to refine its understanding of the user’s preferences and prediction of what the user truly wants. The system is then able to recommend products that may better stimulate the user’s interest in the next interaction cycle. In this paper, we report our extensive investigation of comparing various approaches in devising critiquing opportunities designed in these recommender systems. More specifically, we have investigated two major design elements which are necessary for a critiquing-based recommender system: },
  author = {Chen, Li and Pu, Pearl},
  doi = {10.1007/s11257-008-9057-x},
  interhash = {a9feffd15221c15c499b2ac98ce7d03a},
  intrahash = {f0e063a97473519ca650fe029da73ce7},
  issn = {0924-1868},
  journal = {User Modeling and User-Adapted Interaction},
  language = {English},
  number = 3,
  pages = {167--206},
  publisher = {Springer Netherlands},
  title = {Interaction design guidelines on critiquing-based recommender systems},
  url = {http://dx.doi.org/10.1007/s11257-008-9057-x},
  volume = 19,
  year = 2009
}

@article{alsubaiee2012asterix,
  abstract = {At UC Irvine, we are building a next generation parallel database system, called ASTERIX, as our approach to addressing today's "Big Data" management challenges. ASTERIX aims to combine time-tested principles from parallel database systems with those of the Web-scale computing community, such as fault tolerance for long running jobs. In this demo, we present a whirlwind tour of ASTERIX, highlighting a few of its key features. We will demonstrate examples of our data definition language to model semi-structured data, and examples of interesting queries using our declarative query language. In particular, we will show the capabilities of ASTERIX for answering geo-spatial queries and fuzzy queries, as well as ASTERIX' data feed construct for continuously ingesting data.},
  acmid = {2367532},
  author = {Alsubaiee, Sattam and Altowim, Yasser and Altwaijry, Hotham and Behm, Alexander and Borkar, Vinayak and Bu, Yingyi and Carey, Michael and Grover, Raman and Heilbron, Zachary and Kim, Young-Seok and Li, Chen and Onose, Nicola and Pirzadeh, Pouria and Vernica, Rares and Wen, Jian},
  interhash = {ae521b66302adb1b7df3f4cdb8d92181},
  intrahash = {003f2654ae41861cfb77bf0353634ac3},
  issn = {2150-8097},
  issue_date = {August 2012},
  journal = {Proceedings of the VLDB Endowment},
  month = aug,
  number = 12,
  numpages = {4},
  pages = {1898--1901},
  publisher = {VLDB Endowment},
  title = {ASTERIX: an open source system for "Big Data" management and analysis (demo)},
  url = {http://dl.acm.org/citation.cfm?id=2367502.2367532},
  volume = 5,
  year = 2012
}

@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
}