Data accmulation and fusion system. Seems like an already achieved thing and straightforwardLet me tell you how this is special from other tools out thereAppear Heterogenous (describe)Appear Incremental learning (describe)
Data is no longer homogeneous (it is a combination of images, text, audio)Weave-D supports heterogeneous dataData is no longer available at once, data arrives as streams, at different timesWeave-D can learn incrementallyNot all information is important, user should be able to select which features are importantWeave-D allows user to select important features of data
Would this be better if we present as a 2d flow chart?
Show config filesShow componentsShow as a diagram
Few points about what is the experiment what we’re trying to achieveExploratory mining techniqueVery difficult to measure the qualityBy InspectionCluster PurityShow horizontal not vertical
Sam has an image and he doesn’t know what sport this is. And the images and text files does not have very meaningful filenames. (otherwise he could have guessed the name and found the sport). What Sam can do is, he can query this image from Weave-D and find related images and text both. Then by reading the returned documents, he can figure out the sport.Rename data to have meaningless names!
Few examples explaning the same task Sam querying image and getting text in other domainsEx. Radiologist input and image of a cancer and get the full detailed reports relatedEx. Forensic investigators input an audio clip of a criminal and getting picture of a person as the resultFlexible architectureAllow user to form the architecture!Intuitive UI (Drag & Drop)
NBQSA 2nd round Presentation
Time and Savings Deposits held by the Public
Crime Rate in Sri Lanka
Health Expenditure in Sri Lanka
What is Weave-D?
Inspired by human brain
Data Accumulating, Learning and Fusing
Supports Multimodal data
knowledge to acquire
Come as chunks
Growth of information
What we can mine?
New patient has a cancer or not?
Effective medicine for certain diseases
Diseases distribution in the country
E.g. Anuradhapura – more kidney diseases
Predict customers’ transactional behaviors, so
banks can plan their strategies ahead
Forensics or Police
Predict criminal behavior
Identify crimes with similar
And many more…
Developed by IBM to compete in Jeopardy
A Question answering system
Consumes “millions” of Wikipedia pages and try
to find answers from the knowledge acquired
Finance and health care domains
Learn without forgetting
Support analyzing at
Child (4-8 years old)
Child (8-12 years old)
Child (1-4 years old)
City (Day view)
C5 City (Night view)
Demonstration - Scenario
Sam is a sports enthusiast. He has a set of
images belonging to following sports; Croquet,
Polo, Rock-climbing, Sailing, Rowing,
Badminton. Also he has a small description of
the sport for each image. He needs to cluster
these images and text by the sports category.
All the photos are not available to him at once.
He gets sets of images each day. (Incremental
User’s Point of View
Set of related images and documents explaining the sport
Setting up Weave-D
Querying from Weave-D
Sam doesn’t know what sport this is (Query image)
Meaningless file names!
Get documents explaining the sport denoted by image
What happens inside?
Time Series Links
Agile development – Scrum
Git version controlling
Promotions through Social Media
Advertising on Data Mining websites
Private Investigation Agencies
Few years ahead in Money
Sell 5 units
1 unit = 80K-100K
Sell 10 units
1 unit = 150K-200K
Labor cost (4
Glimpse to the Future
Support mining information at different
Extend Weave-D Client-Server architecture
Support already existing standards (e.g.