IR in HDMs (Liadh Kelly)- 1 - Centre for Digital Video Processing C e n t r e f o r D I g I t a l V...

IR in HDMs (Liadh Kelly) - 1 -

Centre for Digital Video Processing

C e n t r e f o r D I g I t a l V I d e o P r o c e s s I n g

Venturing into the Labyrinth: the Information Retrieval Challenge of

Human Digital Memories

Liadh Kelly Gareth J.F. JonesCentre for Digital Video Processing

Dublin City University




Background and Overview

Overview: • It is now possible to capture and store one’s entire life

experiences in a Human Digital Memory (HDM).

• HDMs are of little use if individuals cannot search through them to find important content.

• We suggest how an individual might search these potentially vast archives of personal information.

•

Human Digital Memory

Computers mobile phones

Cameras video recorders

audio recorders GPS technology

sensor technology …

items read, written, downloaded

footage from life experiences

photographs taken, videos seen, music heard

details of places visited, details of people met …

generated using

containing




HDMs

• HDM - Labyrinth of information:

– Diverse range of item types.– Incompletely linked.– Complex and seemingly unintelligible

labyrinth.

=> new IR techniques required

- Backend algorithms. - User interface.




We propose that rich sources of personal context can be exploited to trigger a person’s memory and to aid retrieval.

Memory & Context Data

Context data:• Users lazy!• Timestamps, GPS technology, Bluetooth, biometric sensors,

data linking.

Last saw photo – sunny day

??

On phone to Jack

Here’s the photo!




Context data

• Timestamps – time of item creation/access.• GPS technology – location of item

creation/access.• Timestamps & GPS – light status and weather

conditions at creation/access time.• Bluetooth tracking – people present at

creation/access time.• Biometric sensors (Polar Heart Rate Monitor,

BodyMedia SenseWear Armband) – arousal, such as excitement or boredom, at creation/access time.




Item Linking

Linking items based on: • Past interactions.• Content & context associations between items.

Context Data Processor

(output: Item & Associated Context

data)

User AccessPatternsDatabase

Item LinkingGenerator

RawContext

Data

ItemCreated

orAccessed

HDM with associated context data and linking

Rememberedcontext

RetrievedItem(s)




Linked Structure

• Link structure used to measure page importance.– e.g. use PageRank to locate

interesting items.

• Linked structure could allow for the suggestion of items which are related (in some sense) to the item currently being examined or worked on.




Interfaces for HDMs

We anticipate that people’s remembering processes can be used as a basis for the design of effective interfaces to aid retrieval from HDMs.

• Great challenge to create interface for the HDM labyrinth, because HDM may be:– vast in size.– item may be labeled with many context features.– item may be linked to large number of other items.– space is personal to the user – may have specific

memory cues that use to recall information.• Interface – intuitive, simple to use, offer required

functionality.

Last saw photo – sunny day

??

On phone to Jack

Here’s the photo!




Sample Prototype Interface

file type

people

access

location

weather

date

recommend

…….………….

A

B

C

D

E

F G

newfavorites




Open Issues

Research Objectives:

• To explore and evaluate the use of existing ranking algorithms, e.g. probabilistic model and PageRank, on HDMs.

• To investigate additional sources of context data.

• To propose new algorithms for effective retrieval from HDMs using context and content.

• To generate test collections and devise experiments to evaluate algorithms.

IR in HDMs (Liadh Kelly)- 1 - Centre for Digital Video Processing C e n t r e f o r D I g I t a l V...

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