How to Lie with Maps

Posted: May 29th, 2006 | 1 Comment »

The (excellent) Map Room has a review today on How to Lie with Maps written by Mark Monmonier.

“[b]ecause most map users willingly tolerate white lies on maps, it’s not difficult for maps also to tell more serious lies” (p. 1).

Relation to my thesis: This concept of white lies on maps tolerated by users can be inspiring on how to play with spatial uncertainty. Back in the days, Darrell Huff’s How to Lie with Statistics was inspiring to me. I would expect a similar relevance from How to Lie with Maps.

Wireless Connection

Posted: May 29th, 2006 | No Comments »

Wireless Connection Instructions Vpn Failure Lost Connection
Wait a minute… I thought all this had to be seamless by now…

Travel-time Maps

Posted: May 26th, 2006 | 1 Comment »

Transport maps and timetables help people work out how to get from A to B using buses, trains and other forms of public transport. In their Travel Time Maps, Chris Lightfoot and Tom Steinberg use colours and contour lines they show how long it takes to travel between one particular place and every other place in the area, using public transport. They also show the areas from which no such journey is possible, because the services are not good enough.

 2006 Travel-Time-Maps Multimodal-Cambridge-Surrounds-1333Px
Cambridge is a small city with a lot of bus services, so it is not very surprising that the whole of the city center and much of the suburbs are within twenty to thirty minutes’ travel of the destination, even including waiting and walking time. Moving further out, though, the picture changes

Related to Distance by the Time of Travel

Relation to my thesis: Interested in ways to visualize mobility. The authors explain the methods they used.

Real-Time Orbiting Objects Tracking

Posted: May 26th, 2006 | No Comments »

J-Track keeps track of orbiting objects (including Mir and Shuttle). It provides a real-time location of a large list of satellites

Related to Flight Tracking

Relation to my thesis: I am interested in real-time tracking of things

Tips for Writing Technical Papers

Posted: May 26th, 2006 | No Comments »

I have 3 papers due for my doctoral school courses on Information Retrieval (Geospatialweb and user context), Artificial Intelligence (not sure yet, but something related to Reinforcement Learning, and Research Seminar (Context driven information supply). Jennifer Widom’s Tips for Writing Technical Papers offers relevant information to structure my assignments.

Relation to my thesis: Learning to write scientific papers

Notes on the Future of Web Search Workshop

Posted: May 26th, 2006 | No Comments »

A few moliskine notes from last week’s Future of Web Search workshop.

From the many diverse talks a few speakers caught my interest including:

Andrei Broder (Yahoo! Research, USA): From query based Information Retrieval to context driven Information Supply Andrei shared his vision of context driven information supply, that is, providing relevant information without requiring the user to make an explicit query (see below).

Andrew Tomkins (Yahoo! Research, USA): Blogs, Friendship and Geography. Analysis of the LiveJournal population based on location and proximity. Mention of “Geo-search”

Nick Craswell (Microsoft Research, UK): Image Search Live. When searching for images people go deeper in the results as for web pages. They read blogs to gather opinions on their implementation of the image search!

Data uncertainty in IR (information retrieval) and databases
I exchanged a few words with Gerhard Weikum from the Max-Planck Institute for Informatics on inferences in search queries and the additional uncertainty in the data that it generates (e.g. does a search on a “professor” also mean to retrieve a “lecturer”?) As I understand handling the mismatch between what is delivered and what is expected is a rather old IR (information retrieval) issue. Somehow, the admitted trade-off is that users willingness to cope with these mismatches is proportional to the value of the seeked information. He pointed me to the work of Jennifer Widom at Stanford on the Trio project, a system for integrated management of data, uncertainty, and lineage. Her group published a couple of papers relevant to my interest:

A. Das Sarma, S.U. Nabar, and J. Widom. Representing Uncertain Data: Uniqueness, Equivalence, Minimization, and Approximation. Technical Report, December 2005.

A. Das Sarma, O. Benjelloun, A. Halevy, and J. Widom. Working Models for Uncertain Data. Proceedings of the Twenty-Second International Conference on Data Engineering, Atlanta, Georgia, April 2006.

User context
The problem of the quality of the retrieved data is twofold. First the algorithm must be able to define relevance out of inferred data. Second how to communicate this relevance to the user based on his own expectations. I raised this question to Andrei Broder from Yahoo! Research who works (user) context driven information supply. He mentioned that it is the job for people of in user experience such as Marc Davis, while I, of course, think that the user’s perspective must already being taken into account in the design of the algorithms. Part of Andrei’s aim is to increase the accuracy of web search results. He defined 3 ways to improve the results:
- Learn a user profile from the interactions
- Define a session profile for each user session
- Use pre-difine word relations (i.e. semantic)

To define profiles there is a need to understand the user context and find the right balance between explicit and implicit queries. My critique of Andrei’s vision is that he wants to infer and push information based on patchy and questionably accurate user contextual data (previous experiences, queries, current location, …) that can misrepresent the user’s intends. As search engines are getting closer to the user (as in ubicomp) it is critical to go beyond database attribute to represent a context. Andrei rightly made fun of the Microsoft Office virtual assistant in form of a paperclip and show other pathetic example of context mismatches. However I am wondering as to how much we have learned from that annoying feature.

When you grow a problem by factor 10, you have a new problem

Somebody mentioned the dynamic of the query, that is the path a user take to improve a query. There is certainly something similar as for dealing with location information.

During the talks wireless microphones lost the connection with the base station. The audio engineer told me it was due to the positions and gestures performed by the speakers and there was not much to do about it. Some much for the “cloud of connectivity”… Even mature technologies sometimes fail to deliver in controlled environments. My thesis has a future!

Back to Romandie…

Posted: May 26th, 2006 | No Comments »

…in an empty plane
Empty Plane2

Animated Map of FedEx Aircraft in Thunderstorm

Posted: May 23rd, 2006 | 1 Comment »

A FAA Radar track sequence of a bank of FedEx aircraft getting into Memphis as thunderstorms pass over the airport

 Blogger 2332 1061 1600 Fedex

Via Cartography

Related to Flight Tracking

From Inaccuracies to Uncertainties

Posted: May 22nd, 2006 | No Comments »

From Gregor Broll’s presentation of Exploiting Seams in Mobile Phone Games at the PerGames 2006 Workshop at the Pervasive, Dublin Ireland

Broll Seamfull

Relation to my thesis: I expect to go deep in defining the technical sources of uncertainties (it might be more than inaccuracies) in order to investigate ways to incorporate spatial uncertainties in the design of ubicomp environments.

Context Awareness via GSM Signal Strength Fluctuation

Posted: May 22nd, 2006 | 1 Comment »

Ian Anderson and Henk Muller. Context Awareness via GSM Signal Strength Fluctuation. In: the 4th International Conference on Pervasive Computing, Late breaking results, pages 27–31. Oesterreichische Computer Gesellschaft, May 2006.

Abstract. In this paper we demonstrate how a cell phone can infer contextual information such as mode of travel by monitoring the fluctuation of GSM signal strength levels and neighbouring cell information. We show that these signals are stable enough to reliably distinguish between various states of movement such as walking, travelling in a motor car and remaining still. We present preliminary results for a metropolitan

Relation to my thesis: I am involved in a similar project that aims at sensing mobility. The authors’ artificial neural network for fusing GSM signals is inspiring. However, it creates occasional errors in detecting the motion. Moreover, as the neural network is adapted to metropolitan areas, an adaptation of its sensitivity would need to be performed for rural areas. Raising the question on how to detect an area.