New papers and updated bibliography

papers/project.bib

@@ -137,6 +137,15 @@
 	using datasets annotated by the subjects themselves.},
   citeulike-article-id = {1188357},
   citeulike-linkout-0 = {http://www.springerlink.com/content/9aqflyk4f47khyjd},
+  comment = {Multiple accelerometers in different locations. Decision-tree classifiers.
+	Some activities are subject-specific.
+	
+	For instance, laboratory acceleration data of walking displays distinct
+	phases of a consistent gait cycle which can aide recognition of pace
+	and incline [2]. However, acceleration data from the same subject
+	outside of the laboratory may display marked fluctuation in the relation
+	of gait phases and total gait length due to decreased self-awareness
+	and fluctuations in traffic.},
   file = {Bao2004.pdf:Bao2004.pdf:PDF},
   keywords = {acceleration},
   owner = {chris},
@@ -417,6 +426,17 @@
   timestamp = {2009.12.01}
 }
 
+@INBOOK{Han2006,
+  chapter = {6},
+  pages = {348-350},
+  title = {Data mining: concepts and techniques},
+  publisher = {Morgan Kaufmann},
+  year = {2006},
+  author = {Han, J and Kamber, M},
+  owner = {chris},
+  timestamp = {2010.01.14}
+}
+
 @MISC{Hein2008,
   author = {Albert Hein and Thomas Kirste},
   title = {Towards Recognizing Abstract Activities: An Unsupervised Approach},
@@ -525,6 +545,32 @@
   url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.39.8472}
 }
 
+@INPROCEEDINGS{Hudson2003,
+  author = {Hudson, Scott and Fogarty, James and Atkeson, Christopher and Avrahami,
+	Daniel and Forlizzi, Jodi and Kiesler, Sara and Lee, Johnny and Yang,
+	Jie},
+  title = {Predicting human interruptibility with sensors: a Wizard of Oz feasibility
+	study},
+  booktitle = {CHI '03: Proceedings of the SIGCHI conference on Human factors in
+	computing systems},
+  year = {2003},
+  pages = {257--264},
+  publisher = {ACM Press},
+   = {New York, NY, USA},
+  citeulike-article-id = {410042},
+  citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=642657},
+  citeulike-linkout-1 = {http://dx.doi.org/10.1145/642611.642657},
+  doi = {10.1145/642611.642657},
+  file = {Hudson2003.pdf:Hudson2003.pdf:PDF},
+  isbn = {1581136307},
+  keywords = {interruptibility, wizard\_of\_oz},
+  owner = {chris},
+  posted-at = {2005-12-04 00:50:45},
+  priority = {0},
+  timestamp = {2010.01.11},
+  url = {http://dx.doi.org/10.1145/642611.642657}
+}
+
 @INPROCEEDINGS{Huynh2005,
   author = {Huynh, T\^{a}m and Schiele, Bernt},
   title = {Analyzing features for activity recognition},
@@ -716,6 +762,43 @@
   url = {http://dx.doi.org/10.1177/0278364907073775}
 }
 
+@ARTICLE{Liao2007b,
+  author = {Liao, Lin and Patterson, Donald J. and Fox, Dieter and Kautz, Henry},
+  title = {Learning and inferring transportation routines},
+  journal = {Artificial Intelligence},
+  year = {2007},
+  volume = {171},
+  pages = {311--331},
+  number = {5-6},
+  month = {April},
+   = {This paper introduces a hierarchical Markov model that can learn and
+	infer a user's daily movements through an urban community. The model
+	uses multiple levels of abstraction in order to bridge the gap between
+	raw GPS sensor measurements and high level information such as a
+	user's destination and mode of transportation. To achieve efficient
+	inference, we apply Rao-Blackwellized particle filters at multiple
+	levels of the model hierarchy. Locations such as bus stops and parking
+	lots, where the user frequently changes mode of transportation, are
+	learned from GPS data logs without manual labeling of training data.
+	We experimentally demonstrate how to accurately detect novel behavior
+	or user errors (e.g. taking a wrong bus) by explicitly modeling activities
+	in the context of the user's historical data. Finally, we discuss
+	an application called "Opportunity Knocks" that employs our techniques
+	to help cognitively-impaired people use public transportation safely.},
+  citeulike-article-id = {1541495},
+  citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1238288},
+  citeulike-linkout-1 = {http://dx.doi.org/10.1016/j.artint.2007.01.006},
+  citeulike-linkout-2 = {http://www.sciencedirect.com/science/article/B6TYF-4N49VP9-1/2/8f05b8caf7327ceb8762ab5e1b95efc9},
+  doi = {10.1016/j.artint.2007.01.006},
+  file = {Liao2007b.pdf:Liao2007b.pdf:PDF},
+  keywords = {learning, statistical-inference},
+  owner = {chris},
+  posted-at = {2008-11-28 02:40:32},
+  priority = {2},
+  timestamp = {2010.01.13},
+  url = {http://dx.doi.org/10.1016/j.artint.2007.01.006}
+}
+
 @ARTICLE{Lukowicz2002,
   author = {Lukowicz, P. and Junker, H. and St\"{a}ger, M. and von B\"{u}ren,
 	T. and Tr\"{o}ster, G.},
@@ -1330,6 +1413,18 @@
   timestamp = {2009.12.03}
 }
 
+@INBOOK{Witten2000,
+  chapter = {3},
+  pages = {72-75},
+  title = {Data Mining: Practical Machine Learning Tools and. Techniques with
+	Java Implementations},
+  publisher = {Morgan Kaufmann},
+  year = {2000},
+  author = {Ian H. Witten and Eibe Frank},
+  owner = {chris},
+  timestamp = {2010.01.14}
+}
+
 @INPROCEEDINGS{Wyatt2007,
   author = {Wyatt, D. and Choudhury, T. and Kautz, H.},
   title = {Capturing Spontaneous Conversation and Social Dynamics: A Privacy-Sensitive
@@ -1366,6 +1461,27 @@
   timestamp = {2009.12.03}
 }
 
+@MISC{ChangeWave2010,
+  title = {http://www.changewaveresearch.com/articles/2010/01/smart\_phone\_20100104.html},
+  owner = {chris},
+  timestamp = {2010.01.12},
+  url = {http://www.changewaveresearch.com/articles/2010/01/smart_phone_20100104.html}
+}
+
+@MISC{ComputerWorld2010,
+  title = {http://www.computerworld.com/s/article/9139026/},
+  owner = {chris},
+  timestamp = {2010.01.12},
+  url = {http://www.computerworld.com/s/article/9139026/Android_to_grab_No._2_spot_by_2012_says_Gartner}
+}
+
+@MISC{TwoFortyFourAm2010,
+  title = {http://www.twofortyfouram.com/},
+  owner = {chris},
+  timestamp = {2010.01.14},
+  url = {http://www.twofortyfouram.com/}
+}
+
 @comment{jabref-meta: selector_publisher:}
 
 @comment{jabref-meta: selector_author:}
@@ -1378,13 +1494,13 @@
 
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-\;Wang2009\;Wyatt2007\;Yang2008\;;
+1 ExplicitGroup:Unread\;0\;Aha1991\;Bardram2005\;Bellotti2008\;Consolv
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