GuideWalk -- Heterogeneous Data Fusion for Enhanced Learning -- A Multiclass Document Classification Case

arXiv:2404.18942v1 Announce Type: cross
Abstract: One of the prime problems of computer science and machine learning is to extract information efficiently from large-scale, heterogeneous data. Text data, with its syntax, semantics, and even hidden information content, possesses an exceptional place among the data types in concern. The processing of the text data requires embedding, a method of translating the content of the text to numeric vectors. A correct embedding algorithm is the starting point for obtaining the full information content …

abstract arxiv case classification computer computer science cs.ai cs.cl cs.lg cs.si data document extract fusion hidden information machine machine learning prime scale science semantics syntax text type types