DIRT maintains accuracy at scale because every contributor needs to deposit tokens to write data. If the data is correct, it is freely shared. If the data is incorrect, anyone can challenge the data and earn tokens for identifying these inaccurate facts. Our protocol and platform makes it economically irrational for misinformation to persist in a data set.
Apache Tika is a toolkit for detecting and extracting metadata and structured text content from various documents using existing parser libraries. For more information about Tika, please see the list of supported document formats and the available documentation . You can find the latest release on the download page . See the Getting Started guide for instructions on how to start using Tika.
Tika is a subproject of Apache Lucene . Lucene is a project of the Apache Software Foundation .
Let's say you've identified a microdecision or two that has economic leverage. What can you do to improve it? There are many possible interventions, and it's important not just to always use the same one. One approach is to automate it entirely. This is the focus of James Taylor and Neil Raden's book Smart Enough Systems, and of Taylor's blog on enterprise decision management. . If the decision is structured enough, that may be a good idea.
T. Mossakowski, and A. Tarlecki. 17th International Conference on Foundations of Software Science and Computation Structures (FoSSaCS), volume 8412 of Lecture Notes in Computer Science, page 441-456. Springer-Verlag Berlin Heidelberg, (2014)
L. Bing, R. Guo, W. Lam, Z. Niu, and H. Wang. Proceedings of the 37th International ACM SIGIR Conference on Research &\#38; Development in Information Retrieval, page 767--776. New York, NY, USA, ACM, (2014)