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In this paper, we describe our ensemble-search based approach, <i>Q</i><sup>2</sup><i>C</i>@<i>UST</i> (<b>http://webprojectl.cs.ust.hk/q2c/</b>), for the query classification task for the KDDCUP 2005. There are two aspects to the key difficulties of this problem: one is that the meaning of the queries and the semantics of the predefined categories are hard(More)
In wireless networks, a client's locations can be estimated using the signals received from various signal transmitters. Static fingerprint-based techniques are commonly used for location estimation, in which a radio map is built by calibrating signal-strength values in the offline phase. These values, compiled into deterministic or probabilistic models,(More)
With the availability of affordable sensors and sensor networks, sensor-based human activity recognition has attracted much attention in artificial intelligence and ubiquitous computing. In this paper, we present a novel two-phase approach for detecting abnormal activities based on wireless sensors attached to a human body. Detecting abnormal activities is(More)
Web-search queries are typically short and ambiguous. To classify these queries into certain target categories is a difficult but important problem. In this article, we present a new technique called query enrichment, which takes a short query and maps it to intermediate objects. Based on the collected intermediate objects, the query is then mapped to(More)
In this paper, we present a novel method to adapt the temporal radio maps for indoor location estimation by offsetting the variational environmental factors using data mining techniques and reference points. Environmental variations, which cause the signals to change from time to time even at the same location, present a challenging task for indoor location(More)
Resistance to platinum drugs has emerged as a major obstacle in the treatment of ovarian cancers. Through proteomic analysis, we have found that the expression of annexin A3, a member of the Ca(2+) and phospholipid-binding annexin family, is significantly increased in platinum-resistant ovarian cell lines. Anti-annexin A3 immunostaining indicated that(More)
Most data mining algorithms and tools stop at discovered customer models, producing distribution information on customer profiles. Such techniques, when applied to industrial problems such as customer relationship management (CRM), are useful in pointing out customers who are likely attritors and customers who are loyal, but they require human experts to(More)
We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to data mining, including uneven sequence lengths, multi-dimensionality and high levels of noise. We adopt a principled approach, by first transforming all the data into an equal-length(More)