Month: January 2008

“X-SOM: Mixing Ontology Mapping Strategies and Consistency Resolution ” Carlo A. Curino, Giorgio Orsi, Letizia Tanca, Poster at European Semantic Web Conferente (ESWC) 2007

“Mining Officially Unrecognized Side effects of Drugs by Combining Web Search and Machine Learning”, Carlo A. Curino, Clement Yu, Yuanyuan Liu, ACM “Conference on Information and Knowledge Management“ CIKM 2005

ABSTRACT:

We consider the problem of finding officially unrecognized side effects of drugs. By submitting queries to the Web involving a given drug name, it is possible to retrieve pages concerning the drug. However, many retrieved pages are irrelevant and some relevant pages are not retrieved. More relevant pages can be obtained by adding the active ingredient of the drug to the query. In order to eliminate irrelevant pages, we propose a machine learning process to filter out the undesirable pages. The process is shown experimentally to be very effective. Since obtaining training data for the machine learning process can be time consuming and expensive, we provide an automatic method to generate the training data. The method is also shown to be very accurate. The side effects of three drugs which are not recognized by FDA are validated by an expert. We believe that the same approach can be applied to many real life problems and will yield high precision. Thus, this could lead a new way to perform retrieval with high accuracy.

BIBTEX:

@inproceedings{1099670,
 author = {Carlo A. Curino and Yuanyuan Jia and Bruce Lambert and Patricia M. West and Clement Yu},
 title = {Mining officially unrecognized side effects of drugs by combining web search and machine learning},
 booktitle = {CIKM '05: Proceedings of the 14th ACM international conference on Information and knowledge management},
 year = {2005},
 isbn = {1-59593-140-6},
 pages = {365--372},
 location = {Bremen, Germany},
 doi = {http://doi.acm.org/10.1145/1099554.1099670},
 publisher = {ACM},
 address = {New York, NY, USA},
 }

“TinyLIME: Bridging Mobile and Sensor Networks through Middleware”, Carlo A. Curino, Matteo Giani, Marco Giorgetta, Alessandro Giusti, Gian Pietro Picco, Amy L. Murphy. IEEE International Conference on Pervasive Computing and Communications. (PerCom) 2005

ABSTRACT:

In the rapidly developing field of sensor networks, bridging the gap between the applications and the hardware presents a major challenge. Although middleware is one solution, it must be specialized to the qualities of sensor networks, especially energy consumption. The work presented here provides two contributions: a new operational setting for sensor networks and a middleware for easing software development in this setting. The operational setting we target removes the usual assumption of a central collection point for sensor data. Instead the sensors are sparsely distributed in an environment, not necessarily able to communicate among themselves, and a set of clients move through space accessing the data of sensors nearby, yielding a system which naturally provides context relevant information to client applications. We further assume the clients are wirelessly networked and share locally accessed data. This scenario is relevant, for example, when relief workers access the information in their zone and share this information with other workers. Our second contribution, the middleware itself is an extension of LlME, our earlier work on middleware for mobile ad hoc networks. The model makes sensor data available through a tuple space interface, providing the illusion of shared memory between applications and sensors. This paper presents both the model and the implementation of our middleware incorporated with the Crossbow Mote sensor platform. 

 BIBTEX: 

@ARTICLE{1392743,
title={TinyLIME: bridging mobile and sensor networks through middleware},
author={Curino, C.; Giani, M.; Giorgetta, M.; Giusti, A.; Murphy, A.L.; Picco, G.P.},
journal={Pervasive Computing and Communications, 2005. PerCom 2005. Third IEEE International Conference on},
year={8-12 March 2005},
volume={},
number={},
pages={ 61-72},
keywords={ ad hoc networks, middleware, mobile computing, shared memory systems, software engineering, wireless sensor networks Crossbow Mote sensor platform, TinyLIME, middleware, mobile ad hoc networks, sensor networks, shared memory, software development, tuple space interface},
doi={10.1109/PERCOM.2005.48},
ISSN={}, }

“The Shining embedded system design methodology based on self dynamic reconfigurable architectures”, Carlo A. Curino, Vincenzo Rana, Marco Domenico Santambrogio, Francesco Redaelli, Donatella Sciuto , to appear at “The 13th Asia and South Pacific Design Automation Conference” (ASP-DAC 2008).

BIBTEX:

@inproceedings{CurinoFRRSS08,
    title = {The Shining embedded system design methodology based on self dynamic reconfigurable architectures.},
    author = {Carlo Curino and Luca Fossati and Vincenzo Rana and F. Redaelli and Marco D. Santambrogio and Donatella Sciuto},
    booktitle = {ASP-DAC},

    pages = {595-600},
    publisher = {IEEE},
    url = {http://dblp.uni-trier.de/db/conf/aspdac/aspdac2008.html#CurinoFRRSS08},
    year = {2008},
    biburl = {http://www.bibsonomy.org/bibtex/22541bd0635aa7c2bf91520d28b65ea40/dblp},
    description = {dblp},
    ee = {http://dx.doi.org/10.1109/ASPDAC.2008.4484021}, date = {2008-05-06},
    keywords = {dblp }
}
 

To appear “And what can Context do for Data?” Cristiana Bolchini, Carlo A. Curino, Giorgio Orsi, Elisa Quintarelli, Rosalba Rossato, Fabio A. Schreiber, Letizia Tanca to appear in the Communication of ACM

 ABSTRACT:

Common to all actors in today’s information world is the problem of lowering the “information noise”, both reducing the amount of data to be stored and accessed, and enhancing the “precision” according to which the available data fit the application requirements. Thus, fitting data to the application needs is tantamount to fitting a dress to a person, and will be referred to as data tailoring. The context will be our scissors to tailor data, possibly assembled and integrated from many data sources. 

“Context Information for Knowledge Reshaping” Cristiana Bolchini, Carlo A. Curino, Elisa Quintarelli, Fabio A. Schreiber, Letizia Tanca, accepted to Journal of Web Engineering and Technology Topic on “Web-based Knowledge Representation and Management”

ABSTRACT:

 2007 campaign. X-SOM is an extensible ontology mapper that combines vari- 

 ous matching algorithms by means of a feed-forward neural network. X-SOM 

 exploits logical reasoning and local heuristics to improve the quality of mappings 

 while guaranteeing their consistency. 

 BIBTEX: