Prof. Zicari interviewed Dr. Alon Y. Halevy, head of the Structured Data Group at Google Research, on Google Fusion Tables and the importance of large scale data management tools.
The full transcript of the interview is available on the ODBMS.org Web site.
Researches from the Search Computing project attended the 11th International Conference on Web Engineering (ICWE 2011) which took place in Paphos (Cyprus) on June 20-24.
Several works has been presented at the conference:
The conference also featured a SeCo-sponsored event: the First International Workshop on Search, Exploration and Navigation of Web Data Sources (ExploreWeb 2011)
Researches from the Search Computing project attended the 2011 ACM SIGMOD Conference, which took place in Athens (Greece) on June 12-16.
A novel, live demonstration of the SeCo Execution Engine and Workbench environment has been presented at a dedicated booth.
DEMONSTRATION
Search Computing: Multi-domain Search on Ranked Data, authored by Alessandro Bozzon, Daniele Braga, Marco Brambilla, Stefano Ceri, Francesco Corcoglioniti, Piero Fraternali, Salvatore Vadacca
Researches from the Search Computing project attended the 2oth International World Wide Web Conference (WWW 2011) which took place in Hyderabad (India) from March 28th to April 1st.
A novel, live demonstration of the Liquid Query search interaction paradigm has been presented at a dedicated booth.
DEMONSTRATION
Exploratory search in multi-domain information spaces with Liquid Query, authored by Alessandro Bozzon, Marco Brambilla, Stefano Ceri, Piero Fraternali, and Salvatore Vadacca.
Do you want to make sense of messy data? Google Refine may prove to be the right tool! It allows for cleaning up messy data, transforming it from one format into another, extending it with web services, and linking it to databases like Freebase.
It takes only 8 minutes to watch the following introductory video!
Do you want to learn more? The next video explains how to transform a wikipage like this into a table by isolating rows of text using a filter and transforming them in one shot using a command.
If you still have time to spent in learning about Google Refine, you may watch the following video. It explains how to augment a dataset with external data. In particular, it shows
Google announced the release of the Shopping API, a new set of Web Application Programming Interfaces that are meant to substitute the existing Google Base APIs. The new Shopping Application Programming Interfaces (APIs) have two main components: Content and Search. Those components are part of a unique CRUD infrustructure for product data management.
On one hand, the Content API enables retailers to upload their product data to Google, and to make incremental updates to frequently changing attributes like price and availability.
On the other hand, the Search API provides access to product data. After creating a new project in the APIs console, a developer can issue JSON queries as the following one:
https://www.googleapis.com/shopping/search/v1/public/products?key=key&country=US&q=digital+camera&alt=atom
This query will return a feed pf products sold in the United States which are all matching the keywords digital and camera. With a registered account, the new Google Shopping API feature a default limit: 2,500 queries/day
The API supports both structured and free text search. Results can be ordered according to relevance, novelty, or price. It is possible to increase diversity in the set of products matching a query by using the APIs crowding mechanism to restrict the number of products with an equivalent property.
The Google Base API will be fully deactivated on June 1, 2011. Some non-shopping data types (such as jobs, real estate, events, and activities) won’t be supported anymore.
Endeca is a US company based in Cambridge, Mass., with operations in North America, Europe, and Asia. Its products portfolio includes a Data Integration and Enrichment platform featuring several interesting data integration functions.
Endeca provides data integration and enrichment capabilities to help you efficiently combine information from any source into a single integrated view and add value on top of the raw data. Our approach to integrating and enriching source data includes the Endeca Content Acquisition System (CAS), an out-of-the-box data integration tool designed for extracting and enhancing both unstructured and structured data, as well as integration points with ETL packages such as Informatica PowerCenter.
Noteworthily, Endeca’s data integration platform shares the same application class space as Search Computing, a fact supported by the the following additional functionality:
Endeca supports the use of joins which allows information from different sources to be combined by any shared attributes across all records. Join support also enables multiple branches of work to converge as appropriate rather than subjecting every record to every possible processing step.
Endeca is recognized as a pioneer of faceted search, particularly in the context of electronic commerce[2] and online libraries[3]. It claims that over 600 customers, including manufacturers, ecommerce sites, media sites, and U.S. intelligence services, are using its Information Access Platform product.
[Source Wikipedia]
[Website www.endeca.com]
Researches from the Search Computing project attended the 8th International Conference on Service Oriented Computing, which took place in San Francisco from December 7 to December 10 2010.
Two works related to Search Computing were presented: a demonstration of the SeCo Execution Engine, and a research paper about the SeCo architecture.
Panta Rhei: Optimized and Ranked Data Processing over Heterogeneous Sources authored by Daniele Braga, Francesco Corcoglioniti, Michael Grossniklaus and Salvatore Vadacca.
Salvatore Vadacca presenting the SeCo demonstration
In the era of digital information, the value of data resides not only in its volume and quality, but also in the additional information that can be inferred from the combination (aggregation, comparison and join) of such data. There is a concrete need for data processing solutions that combine distributed and heterogeneous data sources, such as Web services, relational databases, and even search engines, that can all be modeled as services. In this demonstration, we show how our Panta Rhei model addresses the challenge of processing data over heterogeneous sources to provide feasible and ranked combinations of these services.
A Service-Based Architecture for Multi-domain Search on the Web authored by Alessandro Bozzon, Marco Brambilla, Francesco Corcoglioniti, and Salvatore Vadacca.
Mendeley started as three guys in a virtual garage in 2007 – and has grown to become the world’s largest research collaboration platform less than two years after its public launch in 2008. In 2010, Mendeley cross the barrier of 500,000 users.
Mendeley is a free reference manager and academic social network that can help you organize your research, collaborate with others online, and discover the latest research.
As many other Web 2.0 applications Mendeley also has Web API. Check out Read Meter by Dario Taraborelli for a great mash-up built on them.
The Search Computing website now features 3 additional demonstration videos. The first video demonstrates the Bioinformatic search computing scenario, and it is accessible here.
The remaining 2 videos are the results of a concept design made by 3 Politecnico di Milano students ( Lorenzo Ameri, Marco La Mantia, and Simone Paoli). The application is an “Evening Planner”, and its videos are available here and here.
A screenshot of the Evening Planner demonstration video
