22 Oct 2018
by Janos Szendi-Varga
Knowledge Graph
NLP
Neo4j
Connected Data
Knowledge Platform
Do you think there is no space for a graph database in your company? Or it would be a huge effort to integrate a graph database into your product? I have to tell you: You can use a graph database like Neo4j without touching your product, and you can use it for managing your company’s knowledge as well as to improve your software development process. So, even if your business problem is not inherently graphy (hard to believe in 2018), there are a few reasons why you should think about your environment as a graph.
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26 Sep 2018
by Dr. Alessandro Negro, Dr. Vlasta Kůs
NLP
Knowledge Graph
Sentiment Analysis
word2vec
NER
Data is everywhere. News, blog posts, emails, videos and chats are just a few examples of the multiple streams of data we encounter on a daily basis. The majority of these streams contain textual data – written language – containing countless facts, observations, perspectives and insights that could make or break your business.
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17 Sep 2018
by Dr. Vlasta Kůs, Dr. Alessandro Negro
Sentiment Analysis
doc2vec
NLP
Knowledge Graph
It is often useful to relate a piece of text with the sentiment expressed in it. Extracting and processing sentiments from text provides not only a new emotional access pattern to your corpus but also new knowledge which can reveal new insights. Suppose you want to build a recommendation engine which leverages reviews to spot detailed strengths and weaknesses of different hotels, such as good location but bad staff. Or, it certainly makes a difference whether an article talks about your organization in a positive or negative manner.
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10 Sep 2018
by Dr. Vlasta Kůs, Dr. Alessandro Negro
word2vec
NLP
NER
Knowledge Graph
One of the key components of Information Extraction (IE) and Knowledge Discovery (KD) is Named Entity Recognition, which is a machine learning technique that provides us with generalization capabilities based on lexical and contextual information. Named Entities are specific language elements that belong to certain predefined categories, such as persons names, locations, organizations, chemical elements or names of space missions. They are not easy to find and subsequently classify (for example, organizations and space missions share similar formatting and sometimes even context), but having them is of significant help for various tasks:
- improving search capabilities
- relating documents among themselves or with external information (such as connecting people in a financial document with information from a business registry)
- relating causes (e.g weather conditions, accidents, regulatory changes) with effects (e.g. flight or tram delay, stock price changes)
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03 Sep 2018
by Dr. Vlasta Kůs, Dr. Alessandro Negro
doc2vec
NLP
Knowledge Graph
Representation is one of the most complex and compelling tasks in machine learning. The way in which we represent facts, events, objects, labels, etc. affects how an autonomous learning agent can analyze them and extract insights, make predictions and deliver knowledge.
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05 May 2017
by Alessandro Negro
Neo4j
Elasticsearch
Knowledge Graph
Search
NLP
Recommendations
“Relevance is the practice of improving search results for users by satisfying their information needs in the context of a particular user experience, while balancing how ranking impacts business’s needs.” [1]
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