Refining the process of gathering information

Bombarded by information from numerous sources, many people today turn to electronic news-aggregation services to find what they want. One European team of researchers claims to have developed a flexible and innovative tool that enables journalists and other users to fine-tune the process of news-gathering and delivery.

Early trials of this open-source, distributed system, developed under the IST project PENG, have only recently completed. But coordinator Gabriella Pasi says the participants were impressed with the results.

"Selected Swiss journalists and students assessed the performance of the system's various modules," she says. "For example they checked the effectiveness and accuracy of the information filtering, comparing the results with those from existing systems. They then looked at the integrated system and praised its user-friendliness."

Pasi adds that they liked the system's ability to find relevant information – measured in terms of recall (the proportion of retrieved and relevant documents compared to all documents in the collection) and precision (the ratio of retrieved and relevant documents to all the documents retrieved). A more detailed system trial is due for completion in November 2006.

More than just 'push'
The project originated in research carried out by several partners on information retrieval and filtering. Pasi notes that, "Our project proposal predated the launch of present news-aggregation services, which focus on 'pushing' out information based on user needs." The PENG system, by contrast, offers two distinct techniques: information filtering (push) and information retrieval (pull).

Current news-aggregation systems work very much like internet search engines, pushing out information based on certain user criteria. If users require further filtering, they must create a profile for themselves – which can result in the generation of somewhat limited lists. This process works well for journalists receiving information from online news agencies that produce a continuous news stream; but they still face the problem of selecting the most relevant news.

The PENG system enables users to go much further. By personalising filters, they can pick up targeted information from agencies and combine this with data retrieved from the web or specialised archives. They can also place constraints on the content they seek – such as the media category or trustworthiness of sources – to generate highly specific information. The system then calls on various modules to edit and summarise all this information automatically, before presenting it as the user wishes.

Innovative fuzzy algorithm
Pasi highlights the system's ability to learn user preferences over time. It can also deal with human vagueness or imprecision, such as in the filtering or interaction with the software.

The partners have also developed a new filtering algorithm. Based on categories, it can cluster news from agencies into thematic cluster groups such as sports or politics, for creating data subsets based on common characteristics (e.g. people with a certain hair colour). After these subsets are defined, the system can describe each group (e.g. this is the group with black hair).

"Of the two possible approaches to data clustering," says Pasi, "we chose 'unsupervised' because this approach does not force us to select a priori categories." She adds that the PENG system can display audiovisual content, but works mainly with textual information.

PENG was completed in August 2006. Though the complete system exists only as a prototype, project partner ATOS Origin is examining the possibility of using certain modules in standalone applications. The company is also interested in marketing the project's clustering algorithm, which could be used not only for filtering news but also for image gathering or e-commerce applications.

Contact:
Professor Gabriella Pasi
Consiglio Nazionale Delle Ricerche ITC-CNR
Via Bassini N. 15
I-20131 Milan
Italy
Tel: +39 02 2369 9489
Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Source: IST Results Portal

Most Popular Now

Digital Health Webinar

14 September 2021, Webinar. The digital healthcare ecosystem is evolving with rapid speed. Technologies such as AI, robotics, telemedicine, and precision medicine are a mix of challenges and opportunities...

Using AI for Early Detection and Treatme…

Artificial intelligence (AI) will fundamentally change medicine and healthcare: Diagnostic patient data, e.g. from ECG, EEG or X-ray images, can be analyzed with the help of machine learning, so that...

Waiting Times for Medical Admissions Red…

Clinicians at Bolton NHS Foundation Trust have dramatically reduced patient waiting times, decreased hospital length of stay and improved patient safety after developing an electronic acute medical list solution to manage patient referrals.  The configuration was initially set-up to track referrals and admissions...

AI Algorithm Solves Structural Biology C…

Determining the 3D shapes of biological molecules is one of the hardest problems in modern biology and medical discovery. Companies and research institutions often spend millions of dollars to determine...

Novel AI Blood Testing Technology can ID…

A novel artificial intelligence blood testing technology developed by researchers at the Johns Hopkins Kimmel Cancer Center was found to detect over 90% of lung cancers in samples from nearly...

Accenture HealthTech Innovation Challeng…

Accenture (NYSE: ACN) has named eight companies as finalists in the Accenture HealthTech Innovation Challenge, which brings together leading-edge startups with prominent health companies to tackle some of North America's...

Clinerion Patent for Technology Underpin…

The new Clinerion patent underpins any medical EHR database infrastructure that incorporates a hybrid model of cloud-and-local server node installations at individual hospitals, as well as any method for search...

Data MATRIX Introduces an AI-Operated Pa…

Data MATRIX, a sole Real-World Evidence solutions provider in Russia, has presented a predictive analytics tool for estimating patient survival based on Real-World Data. An important feature of the presented tool for...

Researchers Use AI to Predict which COVI…

Researchers at Case Western Reserve University have developed an online tool to help medical staff quickly determine which COVID-19 patients will need help breathing with a ventilator. The tool, developed through...

A Game Changer: Virtual Reality Reduces …

It isn’t a matter of one needle puncture. Many children coming through the doors of Children's Hospital Los Angeles are seen for chronic conditions and often require frequent visits. Painful...

Bittium Expands Its Minority Holdings in…

Bittium Biosignals Ltd, a subsidiary of Bittium Corporation, and British ECG service provider, Technomed Limited, have today signed an agreement under which Bittium will purchase a 25 percent stake in...

Scientists Develop AI to Predict the Suc…

A study in which machine-learning models were trained to assess over 1 million companies has shown that artificial intelligence (AI) can accurately determine whether a startup firm will fail or...