Document clustering is a significant research issue in information retrieval and text mining. Traditionally, most clustering methods were based on the vector space model which has a few limitations such as high dimensionality and weakness in handling synonymous and polysemous problems. Latent...

The primary goal of an information retrieval system is to retrieve all the documents that are relevant to the user query. Disparities between the vocabulary of the system's authors and that of their users pose difficulties when information is processed without human intervention. Preprocessing...

We present a new approach for content analysis to quantify document tone. We find a significant relation between our measure of the tone of 10-Ks and market reaction for both negative and positive words. We also find that the appropriate choice of term weighting in content analysis is at least...

Donation-based crowdfunding, as part of impact investment, plays a vital role in promoting economic development and alleviating poverty. In order to enhance the lender's enthusiasm for lending behavior, some platforms, for example Kiva, have introduced groups to facilitate lending. This study...

A new, efficient clustering method for solving the cellular manufacturing problem is presented in this paper. The method uses the part-machine incidence matrix of the manufacturing system to form machine cells, each of which processes a family of parts. By doing so, the system is decomposed into...