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Associative networks are a connectionist language model with the ability to handle large sets of documents. In this research we investigated the use of natural language processing techniques (part-of-speech tagging and parsing) in combination with Associative Networks for document categorization and compare the results to a TF-IDF baseline. By filtering out(More)
We demonstrate a new technique for building associative networks based on Wikipedia, comparing them to WordNet-based associative networks that we used previously, finding the Wikipedia-based networks to perform better at document classification. Additionally, we compare the performance of associative networks to various other text classification techniques(More)
Associative networks are a connectionist language model with the ability to categorize large sets of documents. In this research we combine monolingual associative networks based on Wikipedia to create a larger, multilingual associative network, using the cross-lingual connections between Wikipedia articles. We prove that such multilingual associative(More)
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