Comments (1)
Aspect-basedなPDSに関して調査した研究。
たとえば、Wikipediaのクジラに関するページでは、biological taxonomy, physical dimensions, popular cultureのように、様々なアスペクトからテキストが記述されている。ユーザモデルは各アスペクトに対する嗜好の度合いで表され、それに従い生成される要約に含まれる各種アスペクトに関する情報の量が変化する。
UserStudyの結果、アスペクトベースなユーザモデルとよりfitした、擬似的なユーザモデルから生成された要約の方が、ユーザの要約に対するratingが上昇していくことを示した。
また、要約の圧縮率に応じて、ユーザのratingが変化し、originalの長さ>長めの要約>短い要約の順にratingが有意に高かった。要約が長すぎても、あるいは短すぎてもあまり良い評価は得られない(しかしながら、長すぎる要約は実はそこまで嫌いではないことをratingは示唆している)。
Genericな要約とPersonalizedな要約のfaitufulnessをスコアリングしてもらった結果、Genericな要約の方が若干高いスコアに。しかしながら有意差はない。実際、平均して83%のsentenceはGenericとPersonalizedでoverlapしている。faitufulnessの観点から、GenericとPersonalizedな要約の間に有意差はないことを示した。
museum等で応用することを検討
from paper_notes.
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from paper_notes.