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What are the characteristics of semantic or frame network?

What are frame networks?

– Frames that have a digital data transmission unit have got a very important role to play in the computer networking as well as telecommunication.
– This data transmission unit consists of frame synchronization.
– By frame synchronization we mean a sequence of symbols or bits that make it possible for the receiver to know where the data packet begins and end in a stream of bits.
What if we connect a receiver to a system that is located in the middle of frame transmission?
– The device would simply ignore the data until a new synchronization sequence comes in to detection.
– Data packets at the OSI layer 2 are referred to as frames.
– It is essentially a unit of data transmission that consists of the packet following a link–layer header in a link layer protocol.
– Some very popular examples of frame or semantic networks are the Ethernet frames, v. 42 modem frames and PPP frames.
– In TDMA (time division multiple access) and TDM (time – division multiplex) (telecommunications), a frame can be defined as a data block that is repeated over cycles consisting of a certain number of time slots.
– Each of these slots corresponds to each TDMA transmitter or logical DM channel.
– From the viewpoint of this context, a frame can be considered as a physical layer entity.
– Few examples of TDM applications are ISDN circuit switched B – channel and SONET/ SDH.
– On the other hand 2G and 3G circuit switched voice services are examples of TDMA applications.
– The frame also serves as a time – division duplex entity.
– In this, during some time slots the mobile terminal transmits while at the other it receives.

Why frame networks are called as semantic networks?

– Frame networks are also called the semantic networks and these are the ones that show semantic relations between the concepts.
– These networks are also used as some form of knowledge representation.
– It can be defined as an un-directed or a directed graph.
– In these graphs, the vertices represent the edges and the concepts.
– In 1909, a graphical notation of the edges and nodes by the name of ‘existential graphs’ was proposed by Charles S. Peirce.
– It was Richard H. Richens who first invented semantic networks for the computer systems at the Cambridge language research unit for machine translation of the common natural languages.
– One thing about the semantic networks is that they can only be used when one has got knowledge that can be well understood in terms of concepts bearing a relation to one another.
– To say, in general the semantic networks are based up on cognition.
– The arcs and nodes they contain can be arranged in to a taxonomic hierarchy.
– It was the semantic networks that led to the initiation of the inheritance, spreading activation and so on.
– In large domains they are almost intractable.
– Further, they are incapable of representing the Meta – knowledge and performance.

– However, there are some properties that one cannot understand through semantic networks namely:
1. Negation
2. Disjunction
3. General non – taxonomic knowledge

– This is so because these properties require specialized procedures for checking up on them and complimentary predicates and this just reduces the elegance.
– A popular example of semantic framework is the ‘wordNet’.
– It is a lexical database of the English language.
– Its purpose is to sort words in to syn-sets i.e., the set of synonyms.
– WordNet provides short and general definitions of the words.
– Its major purpose is to record all possible semantic relations between these syn-sets.
– Some of the semantic relations are:
1.Meronymy
2.Holonymy
3.Troponymy or hyponymy
4.Hyopernymy
5.Synonymy
6.Antonymy

– Gellish models are also other examples of semantic frameworks.
– There are some elaborate semantic networks developed for lexical knowledge engineering such as the multi-net paradigm, SNePS (semantic network processing system) and so on.
– Semantic networks also find a use in NLP applications.
– Another most common and popular use of the semantic networks is the plagiarism detection.
– They provide info regarding relations so that the semantic compression can be employed.

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