Jong Myoung Kim

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We investigated the notion of " popularity " for machine-generated sentences. We defined a popular sentence as one that contains words that are frequently used, appear in many documents , and contain frequent dependencies. We measured the popularity of sentences based on three components: content morpheme count, document frequency, and dependency(More)
Bactericidal/permeability-increasing protein (BPI) had been shown to possess anti-inflammatory and endotoxin neutralizing activity by interacting with LPS of Gram-negative bacteria. The current study examines the feasibility of using murine BPI (mBPI) expressed on halophilic Archaeal gas vesicle nanoparticles (GVNPs) for the treatment of endotoxemia in(More)
Previous research in spam detection, especially in email spam filtering, mainly focused on learning a set of discriminative features that are often present in the spam contents. Nowadays, these commercially oriented spams are well detected; the real challenge lies in filtering rather vague spams that do not exhibit distinctive spam keywords. We investigate(More)
We apply the notion of “popularity” in machine-generated sentence evaluation to the queries used to search for documents. Our intuition is that queries composed of popular terms obtain more relevant documents and increase the probability that these documents contain the desired results. We measure the popularity of a query by analyzing a(More)
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