vsm :: StringIndex
vsm :: StringIndex :: defaultinit
vsm :: StringIndex :: index_string
Index a new Document fromtitle, uri and string string.
			vsm :: StringIndex :: match_string
Match thequery string against all indexed documents
			vsm :: StringIndex :: parse_string
Parse thestring as a Vector
			vsm $ StringIndex :: SELF
Type of this instance, automatically specialized in every classcore :: Object :: class_factory
Implementation used byget_class to create the specific class.
			vsm :: StringIndex :: defaultinit
vsm :: VSMIndex :: defaultinit
core :: Object :: defaultinit
vsm :: VSMIndex :: index_document
Index a documentvsm :: StringIndex :: index_string
Index a new Document fromtitle, uri and string string.
			vsm :: VSMIndex :: inverse_doc_frequency
Inverse document frequencyvsm :: VSMIndex :: inverse_doc_frequency=
Inverse document frequencyvsm :: VSMIndex :: inversed_index
Inversed indexvsm :: VSMIndex :: inversed_index=
Inversed indexcore :: Object :: is_same_instance
Return true ifself and other are the same instance (i.e. same identity).
			core :: Object :: is_same_serialized
Isself the same as other in a serialization context?
			core :: Object :: is_same_type
Return true ifself and other have the same dynamic type.
			vsm :: StringIndex :: match_string
Match thequery string against all indexed documents
			vsm :: VSMIndex :: match_vector
Matchquery vector to all index document vectors
			core :: Object :: output_class_name
Display class name on stdout (debug only).vsm :: StringIndex :: parse_string
Parse thestring as a Vector
			vsm :: VSMIndex :: terms_doc_count
Count for all terms in all indexed documentsvsm :: VSMIndex :: terms_doc_count=
Count for all terms in all indexed documents
# A VSM index to store strings
class StringIndex
	super VSMIndex
	# Index a new Document from `title`, `uri` and string `string`.
	#
	# Return the Document created.
	#
	# See `index_document`.
	fun index_string(title, uri, string: String, auto_update: nullable Bool): DOC do
		var vector = parse_string(string)
		var doc = new Document(title, uri, vector)
		index_document(doc, auto_update)
		return doc
	end
	# Match the `query` string against all indexed documents
	#
	# See `match_vector`.
	fun match_string(query: String): Array[IndexMatch[DOC]] do
		var vector = parse_string(query)
		var doc = new Document("", "", vector)
		return match_vector(doc.terms_frequency)
	end
	# Parse the `string` as a Vector
	#
	# Returns a vector containing the terms of `string`.
	fun parse_string(string: String): Vector do
		var reader = new StringReader(string)
		var vector = new Vector
		loop
			var token = reader.read_word
			if token == "" then break
			vector.inc(token)
		end
		return vector
	end
end
					lib/vsm/vsm.nit:215,1--253,3