root / tags / 1.0.8 / xapian-core / docs / glossary.rst

Revision 10789, 9.8 kB (checked in by olly, 6 months ago)

Backport change from trunk:
docs/glossary.rst,docs/intro_ir.html: Improve intro_ir a bit, and
link to the definition of RSet in the glossary.

Line 
1.. Copyright (C) 2007 Jenny Black
2.. Copyright (C) 2007 Olly Betts
3.. Copyright (C) 2007 Deron Meranda
4
5========
6Glossary
7========
8
9This glossary defines specialized terminology you may encounter while using
10Xapian.  Some of the entries are standard in the field of Information
11Retrieval, while others have a specific meaning in the context of Xapian.
12
13.. The first sentence should ideally work alone to allow us to reuse these
14.. in the future to generate pop-up information when the user moves the mouse
15.. over the term used in the documentation.
16
17**BM25**
18 The weighting scheme which Xapian uses by default.  BM25 is a refinement on
19 the original probabilistic weighting scheme, and recent TREC tests have shown
20 BM25 to be the best of the known probabilistic weighting schemes.  It's
21 sometimes known as "Okapi BM25" since it was first implemented in an
22 academic IR system called Okapi.
23
24**Boolean Retrieval**
25 Retrieving the set of documents that match a boolean query (e.g. a
26 list of terms joined with a combination of operators such as AND, OR,
27 AND_NOT).  In many systems, these documents are not ranked according to their
28 relevance.  In Xapian, a pure Boolean query may be used, or alternatively a
29 Boolean style query can filter the retrieved documents, which are then ordered
30 using a probabilistic ranking.
31
32**Database**
33 In Xapian (as opposed to a relational database system) a database consists of
34 little more than indexed documents: this reflects the purpose of Xapian as an
35 information retrieval system, rather than an information storage system.
36 These may also occasionally be called Indexes.  Flint is the backend used from
37 Xapian 1.0 onwards, quartz was used in older versions.
38
39**Document ID**
40 A unique positive integer identifying a document in a Xapian database.
41
42**Document data**
43 The document data is one of several types of information that can be
44 associated with each document, the contents can be set to be anything in any
45 format, examples include fields such as URL, document title, and an excerpt of
46 text from the document.  If you wish to interpolate with Omega, it should
47 contain name=value pairs, one per line (recent versions of Omega also support
48 one field value per line, and can assign names to line numbers in the
49 query template).
50
51**Document**
52 These are the items that are being retrieved.  Often they will be text
53 documents (e.g. web pages, email messages, word processor documents)
54 but they could be sections within such a document, or photos, video, music,
55 user profiles, or anything else you want to index.
56
57**Edit distance**
58 A measure of how many "edits" are required to turn one text string into
59 another, used to suggest spelling corrections.  The algorithm Xapian uses
60 counts an edit as any of inserting a character, deleting a character,
61 changing a character, or transposing two adjacent characters.
62
63**ESet (Expand Set)**
64 The Expand Set (ESet) is a ranked list of terms that could be used to expand
65 the original query.  These terms are those which are statistically good
66 differentiators between relevant and non-relevant documents.
67
68**Flint**
69 Flint is the current database format used in Xapian.  It's the default from
70 Xapian 1.0 onwards, replacing Quartz.  Flint is very efficient and highly
71 scalable.  It supports incremental modifications, and concurrent single-writer
72 and multiple-reader access to a database.
73
74**Index**
75 If a document is described by a term, this term is said to index the document.
76 Also, the database in Xapian and other IR systems is sometimes called an index
77 (by analogy with the index in the back of a book).
78
79**Indexer**
80 The indexer takes documents (in various formats) and processes them so that they
81 can be searched efficiently, they are then stored in the database.
82
83**Information Need**
84 The information need is what the user is looking for.  They will usually
85 attempt to express this as a query string.
86
87**Information Retrieval (IR)**
88 Information Retrieval is the "science of search".  It's the name used to
89 refer to the study of search and related topics in academia.
90
91**MSet (Match Set)**
92 The Match Set (MSet) is a ranked list of documents resulting from a query.
93 The list is ranked according to document weighting, so the top document has
94 the highest probability of relevance, the second document the second highest,
95 and so on.  The number of documents in the MSet can be controlled, so it does
96 not usually contain all of the matching documents.
97
98**Normalised document length (ndl)**
99 The normalised document length (ndl) is the length of a document (the number
100 of terms it contains) divided by the average length of the documents
101 within the system.  So an average length document would have ndl equal to 1,
102 while shorter documents have ndl less than 1, and longer documents greater
103 than 1.
104
105**Omega**
106 Omega comprises two indexers and a CGI search application built using the
107 Xapian library.
108
109**Posting List**
110 A posting list is a list of the documents which a specific term indexes.  This
111 can be thought of as a list of numbers - the document IDs.
112
113**Posting**
114 An instance of a particular term indexing a particular document.
115
116**Precision**
117 Precision is the density of relevant documents amongst those retrieved: the
118 number of relevant documents returned divided by the total number of documents
119 returned.
120
121**Probabilistic IR**
122 Probabilistic IR is retrieval based on probability theory, this can produce a
123 ranked list of documents based upon relevance.  Xapian uses probabilistic
124 methods (the only exception is when a pure Boolean query is chosen)
125
126**Quartz**
127 Quartz was the database format used by Xapian prior to version 1.0.  It is
128 now deprecated, and support will be dropped in some future Xapian release.
129 New installations should use Flint, and existing installations should consider
130 migrating to Flint.
131
132**Query**
133 A query is the information need expressed in a form that an IR system can
134 read.  It is usually a text string containing terms, and may include Boolean
135 operators such as AND or OR, etc.
136
137**Query Expansion**
138 Modifying a query in an attempt to broaden the search results.
139
140.. _rset:
141
142**RSet (Relevance Set)**
143 The Relevance Set (RSet) is the set of documents which have been marked by the
144 user as relevant.  They can be used to suggest terms that the user may want to
145 add to the query (these terms form an ESet), and also to adjust term weights
146 to reorder query results.
147
148**Recall**
149 Recall is the proportion of relevant documents retrieved - the number of
150 relevant documents retrieved divided by the total number of relevant
151 documents.
152
153**Relevance**
154 Essentially, a document is relevant if it is what the user wanted.  Ideally,
155 the retrieved documents will all be relevant, and the non-retrieved ones all
156 non-relevant.
157
158**Searcher**
159 The searcher is a part of the IR system, it takes queries and reads the
160 database to return a list of relevant documents.
161
162**Stemming**
163 A stemming algorithm performs linguistic normalisation by reducing variant
164 forms of a word to a common form.  In English, this mainly involves removing
165 suffixes - such as converting any of the words "talking", "talks", or "talked"
166 to the stem form "talk".
167
168**Stop word**
169 A word which is ignored during indexing and/or searching, usually because it
170 is very common or doesn't convey meaning.  For example, "the", "a", "to".
171
172**Synonyms**
173 Xapian can store synonyms for terms, and use these to implement one approach
174 to query expansion.
175
176**Term List**
177 A term list is the list of terms that index a specific document.  In some
178 systems this may be a list of numbers (with each term represented by a number
179 internally), in Xapian it is a list of strings (the terms).
180
181**Term frequency**
182 The term frequency of a specific term is the number of documents in the system
183 that are indexed by that term.
184
185**Term**
186 A term is a string of bytes (often a word or word stem) which describes a
187 document.  Terms are similar to the index entries found in the back of a book
188 and each document may be described by many terms.  A query is composed from
189 a list of terms (perhaps linked by Boolean operators).
190
191**Term Prefix**
192 By convention, terms in Xapian can be prefixed to indicate a field in the
193 document which they come from, or some other form of type information.
194 The term prefix is usually a single capital letter.
195
196**Test Collection**
197 A test collection consists of a set of documents and a set of queries each of
198 which has a complete set of relevance assignments - this is used to test how
199 well different IR methods perform.
200
201**UTF-8**
202 A standard variable-length byte-oriented encoding for Unicode.
203
204**Value**
205 A discrete meta-data attribute attached to a document.  Each document can
206 have many values, each stored in a different numbered slot.  Values are
207 designed to be fast to access during the matching process, and can be used for
208 sorting, collapsing redundant documents, implementing ranges, and other uses.
209 If you're just wanting to store "fields" for displaying results, it's better
210 to store them in the document data.
211
212**Within-document frequency (wdf)**
213 The within-document frequency (wdf) of a term in a specific document is the
214 number of times it is pulled out of the document in the indexing process.
215 Usually this is the size of the wdp vector, but in Xapian it can exceed it,
216 since we can apply extra wdf to some parts of the document text.
217
218**Within-document positions (wdp)**
219 In the case where a term derives from words actually in the document, the
220 within-document positions (wdp) are the positions at which that word occurs
221 within the document.  So if the term derives from a word that occurs three
222 times in the document as the fifth, 22nd and 131st word, the wdps will be 5,
223 22 and 131.
224
225**Within-query frequency (wqf)**
226 The within-query frequency (wqf) is the number of times a term occurs in the
227 query.  This statistic is used in the BM25 weighing scheme.
228
229.. wqp?  nql?  Is it is worth adding these - they're not referenced much.
Note: See TracBrowser for help on using the browser.