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closenesse

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The answer CLOSENESSE has 0 possible clue(s) in existing crosswords.

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The word CLOSENESSE is NOT valid in any word game. (Sorry, you cannot play CLOSENESSE in Scrabble, Words With Friends etc)

There are 10 letters in CLOSENESSE ( C3E1L1N1O1S1 )

To search all scrabble anagrams of CLOSENESSE, to go: CLOSENESSE?

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Scrabble results that can be created with an extra letter added to CLOSENESSE

CLOSENESSES

9 letters out of CLOSENESSE

CLOSENESS COLESSEES SELENOSES

8 letters out of CLOSENESSE

COLESSEE ENCLOSES ESSENCES NOSELESS SOLENESS

7 letters out of CLOSENESSE

ENCLOSE ESSENCE LESSEES LESSENS LESSONS LOESSES SONLESS

6 letters out of CLOSENESSE

CENSES CESSES CLONES CLOSES EOCENE LENSES LEONES LESSEE LESSEN LESSON LOSSES NESSES SCENES SCONES SENSES SOCLES

5 letters out of CLOSENESSE

CENSE CLONE CLONS CLOSE COLES CONES COSES ENOLS ESNES ESSES LENES LENOS LENSE LEONE LESES LOESS LOSES NOELS NOSES SCENE SCONE SEELS SENSE SLOES SOCLE SOLES SONES

4 letters out of CLOSENESSE

CEES CELS CESS CLON COLE COLS CONE CONS COSS EELS ELSE ENOL EONS ESES ESNE LEES LENO LENS LESS LONE LOSE LOSS NESS NOEL NOES NOSE OLES ONCE ONES OSES SECS SEEL SEEN SEES SELS SENE SLOE SOLE SOLS SONE SONS

3 letters out of CLOSENESSE

CEE CEL COL CON COS EEL ELS ENS EON ESS LEE LES NEE NOS OES OLE ONE ONS OSE SEC SEE SEL SEN SOL SON SOS

2 letters out of CLOSENESSE

EL EN ES LO NE NO OE ON OS SO

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Definitions of closenesse in various dictionaries:

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Closenesse might refer to
In a connected graph, Closeness centrality (or closeness) of a node is a measure of centrality in a network, calculated as the reciprocal of the sum of the length of the shortest paths between the node and all other nodes in the graph. Thus, the more central a node is, the closer it is to all other nodes.
* Closeness was defined by Bavelas (1950) as the reciprocal of the farness, that is:*
*
*
* C
* (
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* =
*
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* 1
*
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* ∑
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* .
*
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* {\displaystyle C(x)={\frac {1}{\sum _{y}d(y,x)}}.}
* where
*
*
*
* d
* (
* y
* ,
* x
* )
*
*
* {\displaystyle d(y,x)}
* is the distance between vertices
*
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* {\displaystyle x}
* and
*
*
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* y
*
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* {\displaystyle y}
* . When speaking of closeness centrality, people usually refer to its normalized form which represents the average length of the shortest paths instead of their sum. It is generally given by the previous formula multiplied by
*
*
*
* N
* −
* 1
*
*
* {\displaystyle N-1}
* , where
*
*
*
* N
*
*
* {\displaystyle N}
* is the number of nodes in the graph. For large graphs this difference becomes inconsequential so the
*
*
*
* −
* 1
*
*
* {\displaystyle -1}
* is dropped resulting in:
*
*
*
*
* C
* (
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* =
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*
* N
*
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* ∑
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*
*
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* .
*
*
* {\displaystyle C(x)={\frac {N}{\sum _{y}d(y,x)}}.}
* This adjustment allows comparisons between nodes of graphs of different sizes.
* Taking distances from or to all other nodes is irrelevant in undirected graphs, whereas it can produce totally different results in directed graphs (e.g. a website can have a high closeness centrality from outgoing link, but low closeness centrality from incoming links).
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