Knowledge graphs built from Enterprise Social Networks

Photo by Eric Ziegler

More and more companies are building social networks in the enterprise. For those keeping track, the common term used today is Enterprise Social Networks (ESN).In almost all cases, the reasoning for implementing an ESN is to improve collaboration, break down silos, ease the flow information, etc. One that is often missing is how it could influence search results in the enterprise.

In the internet, social networks play a huge role in helping with search results. This help does not come in the straight up indexing of the content and adding to the overwhelming amount of content already being indexed, but rather from the building a a social or knowledge graph from the social networks.

Google, Microsoft, Facebook, etc. have built algorithms to mine the content in social networks and to try to understand the relationships between the interactions happening in the social networks. While this information is used for many purposes, the mining of the data is used build out what is called a social graph and to extend knowledge graphs (think really big taxonomies or ontologies).

There is a big opportunity for companies to leverage their ESN implementations to improve their search results. This concept goes beyond the idea of ESN and could even be applied to any location people interact with each other (online meetings, Chat sessions, even corporate email).

By mining the information from these interactions, a social graph of related to topics and concepts can be built, that will improve how people search and eventually find the information they are most interested in.

This note was inspired  +David Amerland book,  Google Semantic Search - Amazon location 2111.

The Enterprise Knowledge Graph Grows from the Employee Profile

Photo by Eric Ziegler

This blog post has a little more conceptual thought that will probably require time to read David Amerland's book, Google Semantic Search (see the reference below to get an idea of what I was reading to understand the thoughts in this blog post)

The knowledge graph is a semantic search concept that is all about interpreting what is seen in the internet. The same concepts can be applied to the enterprise, and to be honest is probably a lot easier to do. If I understand how the knowledge graph works, the knowledge graph is built by manually and automatically. The automatic part is completed by the level of trust sites are given and the level of trust of information the search engines find. The knowledge graph is grown over time as it determine what is most trustworthy.

One of the many thoughts I had on the concept of the knowledge graph in the enterprise is that it can be grown systematically based on employee profiles. The links to project sites, links to primary contacts, links to topics that are related are often found in employee profiles. So Building out an enterprise profile is key to creating a social network of connections. The profile is a key piece of information that can help the knowledge graph grow - growing through the connections of topics to employees and employees to employees and then back from employees to topics.

This note was inspired by +David Amerland 's book, Google Semantic Search - Amazon location 1727