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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.222.5832
The text was updated successfully, but these errors were encountered:
・MMR #243 をupdate summarization用に拡張.History(ユーザが過去に読んだsentence)の数が多ければ多いほどnon-redundantな要約を出す (Queryに対するRelevanceよりもnon-redundantを重視する) ・Historyの大きさによって,redundancyの項の重みを変化させる. ・MMRのredundancyの項を1-max Sim2(s, s_history)にすることでnoveltyに変更.ORよりANDの方が直感的なので二項の積にする. ・MMRのQueryとのRelevanceをはかる項のSimilarityは,cossimとJaro-Winkler距離のinterpolationで決定. Jaro-Winkler距離とは,文字列の一致をはかる距離で,値が大きいほど近い文字列となる.文字ごとの一致だけでなく,ある文字を入れ替えたときにマッチ可能かどうかも見る.一致をはかるときはウィンドウを決めてはかるらしい.スペルミスなどの検出に有用.クエリ内の単語とselected sentences内の文字列のJaro-Winkler距離を計算.各クエリごとにこれらを求めクエリごとの最大値の平均をとる. ・冗長性をはかるSim2では,normalized longest common substringを使う.
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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.222.5832
The text was updated successfully, but these errors were encountered: