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GOOGLE KNOWLEDGE GRAPH
- August 28, 2020
- Posted by: Vijin
- Category: Search Engine Optimization
SEO course syllabus there are multiple thinks are included in search engine optimization one of the main feature is KNOWLEDGE GRAPH
The knowledge graph is launched by google on 16th May 2012. It is a system added to google search to provide more useful and relevant results to searches using a semantic search technique. The knowledgebase shows sets of links to external websites, general information such as locations, review, opening hours, etc, and direct answers to questions. The knowledge graph services to enhance its search engine results with information gathered from a variety of sources. It takes data from a variety of sources and presents it in the top right-hand corner of the search page, next to the first few results. It helps searchers can access an answer immediately without needing to click away from google. A knowledge graph is a base of information that offer immediately relevant information related to a specific query.
The knowledge graph involved in two kinds of algorithms, one is used to construct it and another one is used to query it. The construction algorithms are used to connect unstructured information sources into a graph of concept or entities. The relationship between the concepts and the attributes of each concept. In knowledge graph, the query algorithm are used to find the relevant concept in order to answer user’s questions. These are likely to involve some disambiguation, determining the content of a query ,and associated each criteria specified to the corresponding attributes in the knowledge base.
There are 4 main techniques to knowledge representation. Logical, Semantic,Frame and Production rules.
Logical representation is a language which represents a conclusion based on various conditions. It has some definite rules that deal with propositions. Logic representation is the basic of the programming languages, which helps to perform logical reasoning. Logical representation have some restrictions because this technique may not be very natural. The efficiency of inference is not very good.
Semantic network representation is the alternative of logic representation. In semantic network representation, the knowledge is represented as a graphical network. This network consists of nodes representing objects and arcs which give the relationship between those objects. Semantic networks are a natural representation of knowledge. It helps to convey meaning in a transparent form that simple and easy to understand. A semantic network has some disadvantages. Semantic networks are not intelligent and it takes more computational time at runtimes. It depends on the creator of the system. These are inadequate as they do not have any equivalent quantifies.
Frame representation is a record like structure that includes a collection of attributes and values to describes an entity in the world. There are the data structures that are used to divide knowledge into substructures. Stereotype situations are represented by substructures. It contains many slots and slot values of any type and size. Each slot has names and values that are called facets. Frame representation is an easy way to understand and visualize. It is easy to add slots for new attributes and relations. It makes the program easier by grouping the related data. There are some disadvantages to frame representation. It is a very generalized approach. The mechanism cannot be easily processed in the frame system inference. The process of inference mechanism is not easy in frame representation.
The production rules are highly modular. It has two-part, the condition part of the rule is to determine which rule is applied to a problem. The action part is associated with problem-solving steps. In production rules, agent checks for the condition, and if the condition exists then production rule is processed and corresponding action is carried out. The production rule system containing three main parts, The set of production rules, working memory and the recognize act cycle. The rule-based production systems are inefficient, because many rules may active during the execution of the programme. There are multiple kinds of rules in digital marketing trends . and to know more about TOP 10 TRAINING INSTITUTES FOR DIGITAL MARKETING COURSES in India please visit our website https://learndigital.co/blog