文件類別整合(簡稱類別整合)在許多電子商務的應用上是十分重要的，包括中介者的資訊收集以及供應鏈管理的整合等等。由於全球化的趨勢，類別整合的需求由單語延伸至多語。多語類別整合的目標在於整合兩個文件目錄，每個目錄都包含了由不同語言寫成的文件。目前有幾個類別整合的技術已經在文獻中被提出，但是這些技術將重點放在單語類別整合而非多語類別整合。本研究首先提出了一個特徵加強的多語類別整合技術(簡稱FR-PLCI)，當來源目錄中的文件要被整合進目標目錄中時，會考慮到目標目錄中所有語言的文章。接著我們發展出另外兩個延伸的特徵加強多語類別整合技術，也就是以文件加強多語類別整合(簡稱DE-PLCI)技術以及機率加強類別整合(簡稱PE-PLCI)技術，將經過FR-PLCI整合完畢的來源目錄中的文章，加入此兩種技術的起始流程，以重複進行的方式反覆操作特徵加強的多語類別整合流程。利用單語的類別整合技術作為評估成效的基準，我們的實驗結果顯示，不論是在英文或是中文的類別整合實驗，本研究所提出的特徵加強多語類別整合技術與單語類別整合技術相較之下可達到較高的整合準確度。另外，DE-PLCI以及PE-PLCI技術的實驗結果顯示，當兩個目錄相似度在中上程度時，能夠改善原本的特徵加強多語類別整合技術。

Document-category integration (or category integration for short) is fundamental to many e-commerce applications, including information aggregation by intermediaries and integration of supply chain management. Because of the trend of globalization, the requirement for category integration has been extended from monolingual to poly-lingual settings. Poly-lingual category integration (PLCI) aims to integrate two document catalogs, each of which consists of documents written in a mix of languages. Several category integration techniques have been proposed in the literature, but these techniques focus only on monolingual category integration rather than PLCI. In this study, we first propose a feature-reinforcement-based PLCI (namely, FR-PLCI) technique that takes into account the master documents of all languages when integrating a source catalog into the master catalog. Furthermore, we also develop two extended FR-PLCI techniques (referred to as the DE-PLCI and PE-PLCI techniques) that employ integrated source documents into the FR-PLCI process in an iterative manner. Using the monolingual category integration technique (MnCI) as performance benchmarks, our empirical evaluation results show that our proposed FR-PLCI technique achieves higher integration accuracy than MnCI does in both English and Chinese category integration. In addition, the extended FR-PLCI techniques (i.e., DE-PLCI and PE-PLCI) generally improve the performance of FR-PLCI in the homogeneous and comparable scenario.

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