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Titlebook: On Global Univalence Theorems; T. Parthasarathy Book 1983 Springer-Verlag Berlin Heidelberg 1983 Differenzierbare Abbildung.Finite.Funktio

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發(fā)表于 2025-3-21 17:18:16 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱On Global Univalence Theorems
編輯T. Parthasarathy
視頻videohttp://file.papertrans.cn/701/700994/700994.mp4
叢書(shū)名稱Lecture Notes in Mathematics
圖書(shū)封面Titlebook: On Global Univalence Theorems;  T. Parthasarathy Book 1983 Springer-Verlag Berlin Heidelberg 1983 Differenzierbare Abbildung.Finite.Funktio
出版日期Book 1983
關(guān)鍵詞Differenzierbare Abbildung; Finite; Funktionaldeterminante; Globale Eindeutigkeit; Inverse Funktion; Morp
版次1
doihttps://doi.org/10.1007/BFb0065566
isbn_softcover978-3-540-11988-3
isbn_ebook978-3-540-39462-4Series ISSN 0075-8434 Series E-ISSN 1617-9692
issn_series 0075-8434
copyrightSpringer-Verlag Berlin Heidelberg 1983
The information of publication is updating

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發(fā)表于 2025-3-21 22:22:01 | 只看該作者
T. Parthasarathysode mining strategies have been suggested, which can be roughly classified into two classes: Apriori-based breadth-first algorithms and projection-based depth-first algorithms. As we know, both kinds of algorithms are level-wise pattern growth methods, so that they have higher computational overhea
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地板
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發(fā)表于 2025-3-22 09:13:34 | 只看該作者
T. Parthasarathyf the data sources. However, keyword queries are usually ambiguous in expressing the user intent. Most of the current keyword search approaches either filter or use a scoring function to rank the candidate result set. These techniques do not differentiate the results and might return to the user a r
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發(fā)表于 2025-3-22 17:27:58 | 只看該作者
T. Parthasarathy a big challenge in real-world applications due to the sparse, noisy and ambiguous nature of queries. In this paper, we present another important issue called “the pomegranate phenomenon”. This phenomenon is named for the gap between manually manageable small taxonomy and massive coherent topics in
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發(fā)表于 2025-3-23 05:00:49 | 只看該作者
T. Parthasarathyrative filtering recommender systems are highly vulnerable to “shilling” attacks due to its openness. Although attack detection based on such attacks has been extensively researched during the past decade, the studies on these issues have not reached an end. They either extract extra features from u
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