Skip to main content

Knowledge Graph



What is Knowledge Graph?

Google is using knowledge Graphs to enhance it's Google search results. For this purpose it is exploiting information from a wide variety of sources which includes data from various websites like Freebase, Wikipedia and others. The data that is used has information about people, events, environment, cultural and historical happenings.

What Google's Knowledge graph do?

  • The box in the right side of the Google search page is delivered as a result of the search using Google's Knowledge Graph.



  • The top box showing the concise form of result when asked a question in Google search is also delivered through Knowledge Graph.



  • Knowledge graphs are also used when we have search queries like top movies, songs, novels etc or list of latest books etc.

     

  • Most often the answers that are used by Google Assistant are kind of summary of the search using knowledge Graph.

How it works?

Semantic information is collected from various and varied sources, so that the content is rich. Graph data stricture and list is used by Knowledge graphs. Graphs stores the interlinking of information from sources and list stores external lists to websites if any. As the end of 2016, Knowledge Graph holds over 70 billion facts.

Other companies' knowledge graphs:

  • Microsoft Bing's Satori Knowledge Base, revealed to the public in mid-2013
  • Yandex's Object Answer (ru), released in 2015
  • Yahoo! and Baidu also have such technologies.
  • LinkedIn's Knowledge Graph, revealed to the public in Oct 2016. It is a dynamic graph updated in real time upon member profile changes and when new entities emerge.

Refrences

Comments

Post a Comment

Popular posts from this blog

NLP in Video Games

From the last few decades, NLP (Natural Language Processing) has obtained a high level of success in the field  of Computer Science, Artificial Intelligence and Computational Logistics. NLP can also be used in video games, in fact, it is very interesting to use NLP in video games, as we can see games like Serious Games includes Communication aspects. In video games, the communication includes linguistic information that is passed either through spoken content or written content. Now the question is why and where can we use NLP in video games?  There are some games that are related to pedagogy or teaching (Serious Games). So, NLP can be used in these games to achieve these objectives in the real sense. In other games, one can use the speech control using NLP so that the player can play the game by concentrating only on visuals rather on I/O. These things at last increases the realism of the game. Hence, this is the reason for using NLP in games.  We ...
4 comments
Read more

Word embeddings and an application in SMT

We all are aware of (not so) recent advancements in word representation, such as Word2Vec, GloVe etc. for various NLP tasks. Let's try to dig a little deeper of how they work, and why they are so helpful! The basics, what is a Word vector? We need a mathematical way of representing words so as to process them. We call this representation, a word vector. This representation can be as simple as a one-hot encoded vector having the size of the vocabulary.  For ex, if we had 3 words in our vocabulary {man, woman, child}, we can generate word vectors in the following manner Man : {0, 0, 1} Woman : {0, 1, 0} Child : {1, 0, 0} Such an encoding cannot be used to for any meaningful comparisons, other than checking for equality. In vectors such as Word2Vec, a word is represented as a distribution over some dimensions. Each word is assigned some particular weight for each of the dimensions. Picking up the previous example, this time the vectors can be as following (assuming a 2 dime...
1 comment
Read more

Discourse Analysis

NLP makes machine to understand human language but we are facing issues like word ambiguity, sarcastic sentiments analysis and many more. One of the issue is to predict correctly relation between words like " Patrick went to the club on last Friday. He met Richard ." Here, ' He' refers to 'Patrick'. This kind of issue makes Discourse analysis one of the important applications of Natural Language Processing. What is Discourse Analysis ? The word discourse in linguistic terms means language in use. Discourse analysis may be defined as the process of performing text or language analysis, which involves text interpretation and knowing the social interactions. Discourse analysis may involve dealing with morphemes, n-grams, tenses, verbal aspects, page layouts, and so on. It is often used to refer to the analysis of conversations or verbal discourse. It is useful for performing tasks, like A naphora Resolution (AR) , Named Entity Recognition (NE...
5 comments
Read more