Donnie H. Kim, Kyungsik Han, Deborah Estrin UCLA CSD CENS Ubicomp 2011 EMPLOYING USER FEEDBACK FOR...
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Donnie H. Kim, Kyungsik Han, Deborah Estrin
UCLA CSD CENS
Ubicomp 2011
EMPLOYING USER FEEDBACK FOR SEMANTIC LOCATION SERVICES
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SEMANTIC LOCATION SERVICES• Numerous emerging applications want colloquial places and paths rather than just
coordinates
• E.g., personal application such as geo-reminder and location diaries
• Social applications such as whereabout-sharing and ride-sharing
• People normally think and speak locations in terms of places like “my home” or “Ed’s office”
• Location-aware applications encounter the problem of translating coordinates provided by today’s position systems to semantic places
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CHALLENGES• Current location-aware applications must handle the coordinates directly
• Absence of a universal place database
• Force users to define places one-by-one by drawing circles on a map
• Such schemes fail in describing many interesting indoor places and poorly scale
• Creating indoor localization in every building is currently far-fetched
• Relying on users to delineate places from scratch can omit many interesting places
• Continuously estimating absolute positions significantly impacts battery-life on the mobile device
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LOCI• A service layer that abstracts a user’s location context as places and paths
• The service
• Learns new places
• Suggests potentially meaningful places
• Recognizes registered places
• Tracks paths connecting places
• Employing user feedback
• Managing suggested places
• Telling when the service detects places incorrectly
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WHAT TO UNDERSTAND• What to understand
• How often user feedback is needed
• What helps a user manage suggested places
• How we can encourage a user to provide feedback to the service
• Three-week user study with 29 participants
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LOCI SEMANTIC LOCATION SERVICE ARCHITECTURE
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HOW TO OPERATE• Initially, no places are registered with the service
• As the user carries around the mobile device running Loci, new places are gathered as potential everyday places waiting to be reviewed and confirmed
• Places are suggested when the user visits them for the first time and spends a substantial amount of time
• Loci automatically infers entrance to and exit from a place using Wi-Fi fingerprints
• Loci provides the user for recent visit times, approximate position of the place, and a list of neighboring Wi-Fi access point names as hints
• To assist the user in deciding if a place is valid
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USER INTERFACE
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VIEW• Calendar view
• View place visit histories in a calendar which consists of a monthly view and a daily view
• Map view
• Let a user view location trajectories of a selected day on a map
• List view
• View places by its status: registered, suggested, and blocked
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EMBEDDED SURVEY TOOLS• Place surveys
• To characterize places based on user feedback
• Users take a survey about a particular place by choosing a place from the registered place list
• A user selects a name category of the chosen place name, add keywords, report place-detection failures, and writes free-text comments
• Daily surveys
• To understand how often a user may need to report about failures
• If any discrepancies between what Loci detects and what the user remembers are noticed during a day, they are reported in the daily surveys
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SERVICE ARCHITECTURE• Place handler
• Detect place visits by periodically scanning neighboring Wi-Fi APs
• Initiate path handler as the user leaves the place
• Path handler
• Track positions using the GPS module
• Movement handler
• Find opportunities to save energy while the device is staying at a place and immobile
• Data storage
• Maintain places, visit histories, tracks, and survey answers
• Upload handler
• Triggered when the phone is plugged-in to a power outlet
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USER STUDY RESULTS• Research questions guided Loci design
• How often does a user need to provide feedback?
• What helps a user manage suggested places?
• How can we motivate a user to provide feedback?
• 29 participants
• Three week
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USER FEEDBACK DEMANDS:REGISTERING NEW PLACES• Average number of suggested places a user received
• Average number of visits per day by user
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USER FEEDBACK DEMANDS:REPORTING PLACE FAILURES
Freq. Missed Divided Merged Wrong
Never 845 (97.3%) 793 (91.4%) 844 (97.2%) 850 (97.9%)
Sometimes 20 (2.3%) 54 (6.2%) 20 (2.3%) 16 (1.8%)
Often 3 (0.4%) 17 (1.9%) 3 (0.4%) 1 (0.1%)
Always 0 (0%) 4 (0.5%) 1 (0.1%) 1 (0.1%)
Total 868 (100%) 868 (100%) 868 (100%) 868 (100%)
• 176 daily surveys from 29 participants
• 51% of the participants submitted every day
• 27% reported once a day more
• 21% submitted none
• 868 place surveys from 29 participants
• Divided at relatively large spaces where a single Wi-Fi fingerprint couldn’t cover the entire space
• E.g., department store, music hall
• Merged when a user directly moved from one place to another separated by a single floor or a hallway
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MANAGING SUGGESTED PLACES• Users usually selected either calendar view or list view to review new places
• Map view was used rarely
• Calendar view: people thought viewing place visits in a chronological order was helpful in remembering places
• List view: it is easier to view every suggested places in one places
• Map failed to provide enough information in cases where the GPS provided largely inaccurate indoor position estimation
• In what order they consulted the hints
• 42%, time map wifi
• 31%, map time wifi
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ENCOURAGING USER FEEDBACK• Key implication to the semantic location services
• People are generally open to providing feedback to improve the service
• Well-timed notifications and informative feedback motivates users to provide more input
• Post-study exit survey
• Mostly positive about receiving suggested places and managing personal places
• Maximum number of suggested places a participant will handle per day
• 32%, the number doesn’t really matter
• 50%, four or above
• 28%, three or above
• Providing other contextual information about the visit or adding a social component may encourage them to engage more
• The most desired feature: getting reminders about new suggestions
• 75% thought they would register more places if Loci prompted when new places appeared
• 46% wanted to be prompted they were at the new place
• 36% preferred to be prompted when arriving at home in the evening
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RESOURCE USAGE• Energy consumption
• Daily average sensor on-time by participant
• Memory usage
• 0.25MB per day on average
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•Thank you.