Taylor and Joudrey (2012) concluded their book, *The Organization of Information*, by stating that there is much work to be done in both information organization and the development of retrieval systems. 1,235 more words

## Tags » Knowledge Discovery

#### The Organization of Information

#### Advances in Social Network Analysis and Mining Conference -- Sydney

This conference will be in Sydney in 2017, from 31st July to 3rd August.

http://asonam.cpsc.ucalgary.ca/2017/

As well as the main conference, there is also a workshop, FOSINT: Foundations of Open Source Intelligence, which may be of even more direct interest for readers of this blog. 15 more words

#### Implementing Fuzzy Sets in SQL Server, Part 8: Possibility Theory and Alpha Cuts

**By Steve Bolton**

…………To get the point across that fuzzy sets require membership grades of some sort, throughout this series I’ve borrowed the stored procedure I coded for… 2,249 more words

#### Implementing Fuzzy Sets in SQL Server, Part 7: The Significance of Fuzzy Stats

**By Steve Bolton**

…………In the world of fuzzy sets and imprecision modeling, the concept of cardinality takes on new shades of meaning that are not applicable to ordinary “crisp” sets, i.e. 2,636 more words

#### Implementing Fuzzy Sets in SQL Server, Part 6: Fuzzy Numbers and Linguistic Modifiers

**By Steve Bolton**

…………I’ve written several amateur tutorial series on this blog in order to more quickly absorb difficult data mining, statistical and machine learning topics, while hopefully helping other SQL Server users avoid some of my inevitable mistakes. 2,482 more words

#### Implementing Fuzzy Sets in SQL Server, Part 5: The Mystery of the Missing Left Join

**By Steve Bolton**

…………Information on set operations like complements, intersections and unions is plentiful in the literature on fuzzy sets, which made the last three articles in this series of amateur self-tutorials easier to write in a certain sense. 2,053 more words

#### Implementing Fuzzy Sets in SQL Server, Part 4: From Fuzzy Unions to Fuzzy Logic

**By Steve Bolton**

…………Fuzzy set relations carry an added layer of complexity not seen in ordinary “crisp” sets, due to the need to derive new grades for membership in the resultset from the scores in the original sets. 4,044 more words