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Titlebook: Legal Language and Business Communication; Anurag K. Agarwal Book 2019 The Editor(s) (if applicable) and The Author(s), under exclusive li

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21#
發(fā)表于 2025-3-25 05:19:56 | 只看該作者
Anurag K. Agarwale 16th International Conference of Inductive Logic Programming (ILP 2006) was a radical (hopefully interesting but not cursed) departure from previous years. Submissions were requested in two phases. The ?rst phase involved submission of short papers (three pages) which were then presented at the co
22#
發(fā)表于 2025-3-25 09:36:17 | 只看該作者
23#
發(fā)表于 2025-3-25 14:47:24 | 只看該作者
Anurag K. Agarwalther unspecific way. That is, they do not construct features “on demand”, but rather in advance and without detecting the need for a representation change. Even if structural features are required, current methods do not construct these features in a goal-directed fashion..In previous work, we prese
24#
發(fā)表于 2025-3-25 19:40:22 | 只看該作者
Anurag K. Agarwalper or linguist. In this work, we present the use of two Inductive Logic Programming (ILP) techniques to construct rules for extracting instances of various named entity classes thereby reducing the efforts of a linguist/developer. Using ILP for rule development not only reduces the amount of effort
25#
發(fā)表于 2025-3-25 20:03:34 | 只看該作者
Anurag K. Agarwalis delegated to statistical multi-instance learning schemes. To each clause, there is an associated multi-instance classification model with the numerical variables of the clause as input. Clauses are built in a greedy manner, where each refinement adds new numerical variables which are used additio
26#
發(fā)表于 2025-3-26 02:02:48 | 只看該作者
Anurag K. Agarwalarget-specific inhibitors. This form of drug-design is assuming increasing importance with the advent of new disease threats for which known chemicals only provide limited information about target inhibition. In this paper, we propose the combined use of deep neural networks and Inductive Logic Prog
27#
發(fā)表于 2025-3-26 06:24:32 | 只看該作者
Anurag K. Agarwale .2. algorithm. Usually, it has been found that using an embedded representation results in much better performance for the task being addressed. It is not known whether embeddings can similarly improve performance with data of the kind considered by Inductive Logic Programming (ILP), in which data
28#
發(fā)表于 2025-3-26 10:41:04 | 只看該作者
Book 2019o the law, those limits are not readily visible to the uninitiated; occasionally, even experts flounder. Exploring precisely these topics, the book will be of interest to students of business, law, and business communication; managers; lawyers; researchers; practitioners; and general readers alike..
29#
發(fā)表于 2025-3-26 13:27:15 | 只看該作者
30#
發(fā)表于 2025-3-26 20:32:15 | 只看該作者
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