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

AI Catches One-Third of Interval Breast …

An AI algorithm for breast cancer screening has potential to enhance the performance of digital breast tomosynthesis (DBT), reducing interval cancers by up to one-third, according to a study published...

Great plan: Now We need to Get Real abou…

The government's big plan for the 10 Year Health Plan for the NHS laid out a big role for delivery. However, the Highland Marketing advisory board felt the missing implementation...

Researchers Create 'Virtual Scienti…

There may be a new artificial intelligence-driven tool to turbocharge scientific discovery: virtual labs. Modeled after a well-established Stanford School of Medicine research group, the virtual lab is complete with an...

From WebMD to AI Chatbots: How Innovatio…

A new research article published in the Journal of Participatory Medicine unveils how successive waves of digital technology innovation have empowered patients, fostering a more collaborative and responsive health care...

New AI Tool Accelerates mRNA-Based Treat…

A new artificial intelligence (AI) model can improve the process of drug and vaccine discovery by predicting how efficiently specific mRNA sequences will produce proteins, both generally and in various...

Can Amazon Alexa or Google Home Help Det…

Computer scientists at the University of Rochester have developed an AI-powered, speech-based screening tool that can help people assess whether they are showing signs of Parkinson’s disease, the fastest growing...

AI also Assesses Dutch Mammograms Better…

AI is detecting tumors more often and earlier in the Dutch breast cancer screening program. Those tumors can then be treated at an earlier stage. This has been demonstrated by...

RSNA AI Challenge Models can Independent…

Algorithms submitted for an AI Challenge hosted by the Radiological Society of North America (RSNA) have shown excellent performance for detecting breast cancers on mammography images, increasing screening sensitivity while...

AI could Help Emergency Rooms Predict Ad…

Artificial intelligence (AI) can help emergency department (ED) teams better anticipate which patients will need hospital admission, hours earlier than is currently possible, according to a multi-hospital study by the...

Head-to-Head Against AI, Pharmacy Studen…

Students pursuing a Doctor of Pharmacy degree routinely take - and pass - rigorous exams to prove competency in several areas. Can ChatGPT accurately answer the same questions? A new...

NHS Active 10 Walking Tracker Users are …

Users of the NHS Active 10 app, designed to encourage people to become more active, immediately increased their amount of brisk and non-brisk walking upon using the app, according to...

The Human Touch of Doctors will Still be…

AI-based medicine will revolutionise care including for Alzheimer’s and diabetes, predicts a technology expert, but it must be accessible to all patients. Healing with Artificial Intelligence, written by technology expert Daniele...