Search

Social media users have been growing exponentially in recent years. This growth has evoked researchers and manager to analyze the social media and customer sentiment because it offers significant opportunities to advance business intelligence in supply chain. However, supply chain members are struggling in understanding the general sentiments in today’s business world. Therefore, various methods are used to provide valuable insights in supply chain. In this paper, SentiStrength is used to analyze customer reviews related to one type of product. The output of SentiStrength and demands of the product are then fed into Artificial Neural Network to forecast the customer demands. After, nondominated sorting genetic algorithm II (NSGA-II) based simulation optimization is employed to solve the inventory routing problem using forecasted customer demands. The results of the study demonstrated that the use of hybrid methodology containing sentiment analysis can successfully analyze the inventory routing problem. [ABSTRACT FROM AUTHOR]

Leveraging machine learning techniques in NLP domain has been a very hot research field due to the advancements in artificial intelligence area. Despite the popularity of this field, there is no known study on application of ML techniques on old Turkish language. This study aims to fill in this gap where 32000 pages of text has been downloaded from the websites of Ministry of Culture and a two-layer neural network model has been built on top of them to discover the semantic similarities between Turkish words in old Turkish language. The algorithm has been run with different parameters such as window size, dimension size, sampling size etc. and the produced vector spaces are uploaded into public servers for the purposes of enabling a RESTful API based query interface. Also a web UI has been created to provide a querying mechanism for regular users. The services that are developed can be used for two different purposes. One of them is to integrate these services into existing old Turkish language dictionary websites that are made available by third party providers as well as other institutions such as Ministry of Culture and Turkish Language Institution. Secondly, the developed services are intended to be used for mitigating the translation errors made during the translation of old Turkish texts into modern Turkish language in the areas of history and Turkish literature. Also enabling these services for public use will encourage other researchers to pursue this academic work and compare their results with the experimental results presented in this paper to make further improvements in this field. [ABSTRACT FROM AUTHOR]