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`US 20030046099A1
`
`(19i United StateS
`(12) Patent Application Publication
`Lamont et al.
`
`(Io) Pub. No. : US 2003/0046099 A1
`Mar. 6, 2003
`(43) Pub. Date:
`
`(54) SPATIALLY-BASED VALUATION OF
`PROPERTY
`
`(76)
`
`Inventors:
`
`Ian Gordon Lamont, Coleraine (GB);
`David Joseph McMullan, Articlave
`(GB)
`
`Correspondence Address:
`Ronald W. Citkowski
`Suite 400
`280 N. Old Woodward Avenue
`Birmingham, MI 48009 (US)
`
`(21) Appl. No. :
`
`09/947, 709
`
`(22) Filed:
`
`Sep. 6, 2001
`
`Publication Classification
`
`ABSTRACT
`(57)
`for conducting
`are described
`An apparatus
`and method
`spatially-based valuation of property,
`taking into account the
`values of neighbouring properties. The method proceeds by
`a database of properties
`including details of at
`analysing
`least the location and value of the known properties, and the
`location of the property to be valued. Other characteristics of
`in the database. Similarity
`the properties may be included
`scores for each property compared with each other property
`are calculated, and used to identify
`those properties which
`to be valued. All the com-
`are comparable
`to the property
`parable properties within a predetermined distance from the
`to be valued are used to calculate
`the unknown
`property
`property value.
`
`The method and apparatus may also generate a report on the
`to be valued
`to a user, which report may further
`property
`include details of the comparable properties.
`
`(51) Int. Cl.
`(52) U. S. Cl.
`
`. G06F 17/60
`705/1
`
`A computer program
`described.
`
`for implementing
`
`the method
`
`is also
`
`STARI
`
`to
`
`Add Mapcase /Froiect
`
`Open Vector / Raster Lays s
`
`Open / Import prcperty Dataset
`
`nova Outfiars
`
`Remove Outlrers &
`Update Data set
`
`Create Smilarly
`Index
`FIG 2
`
`Spatial Corrponant
`
`Conpute R. operty
`Value
`FIG 3
`
`Vers Results /Report
`Error Estimatim
`
`Fav isa Criteria
`
`OutputResuts
`
`TRULIA - EXHIBIT 1015
`
`

`

`Patent Application Publication
`
`Mar. 6, 2003 Sheet 1 of 9
`
`US 2003/0046099 A1
`
`START
`
`10
`
`Add Mapbase /Project
`
`12
`
`Open Vector / Fhster Layers
`
`Open/
`
`Import Property Dataset
`
`16
`
`Remve Outliers
`
`18
`
`Remove Outliers 8
`Update Dataset
`
`Create Srnilarty
`Index
`RG2
`
`Select Ares
`
`24
`
`Spatial Corrponent
`
`Con pute R. operty
`Value
`FIG 3
`
`View Results / Report
`&ror Estimation
`
`R vise Criteria
`
`Output Res uks
`
`

`

`Patent Application Publication
`
`Mar. 6, 2003 Sheet 2 of 9
`
`US 2003/0046099 A1
`
`START
`
`34
`
`Select Comp Relds
`
`AIIer Selection
`
`36
`Y
`
`38 + No
`
`Yes
`
`urreric Values
`
`No
`
`Automatic
`R cade
`
`40
`
`Calculate Standardized
`Scores
`
`Create Index of
`Sirri1arity Matrix
`
`Normalize
`
`Index Values
`
`Update Matrix
`
`48
`
`50
`
`FIG 2
`
`

`

`Patent Application Publication
`
`Mar. 6, 2003 Sheet 3 of 9
`
`US 2003/0046099 A1
`
`START
`
`52
`
`Set Comparable R'op.
`
`Select First Sold Property
`
`58
`
`Adjust Sold Value
`
`No
`
`Current Year
`Sale
`
`es
`
`60
`
`Select All Unsold
`Ropeities Wthin
`Radial Distance
`
`62
`
`Corrpare Unsdd to
`Sold Property
`
`Index Value
`Above Threshold
`
`Null Property
`Value
`
`64
`
`68
`
`No
`
`Yes
`
`66
`
`70
`
`Move To N xt
`i@sold Property
`
`Revise Property
`Value
`
`Select hbxt
`Sold Property
`
`+date Property Value
`
`72
`
`Last Sold
`Property
`
`76
`
`80
`
`Store Property Value
`
`ast Unsold
`Property
`
`No
`
`FIG 3
`
`

`

`Patent Application Publication
`
`Mar. 6, 2003 Sheet 4 of 9
`
`US 2003/0046099 A1
`
`96
`
`84
`
`94
`
`Internet
`
`Modem
`
`86
`
`property
`Attribute
`Dataset
`
`88
`
`FlG 4
`
`

`

`Patent Application Publication
`
`Mar. 6 2003 Sh
`eet 5 of 9
`
`7
`
`US 2003/0046099 A1
`
`demo
`
`5elect XCoord Field. . . ,
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`FIG 6
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`

`

`Patent Application Publication
`
`Mar. 6, 2003 Sheet 6 of 9
`
`US 2003/0046099 A1
`
`OEECRPT
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`

`

`Patent Application Publication
`
`Mar. 6, 2003 Sheet 7 of 9
`
`US 2003/0046099 A1
`
`DE5CRPT
`
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`

`

`Patent Application Publication
`
`Mar. 6, 2003 Sheet 8 of 9
`
`US 2003/0046099 A1
`
`Vi
`
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`
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`
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`
`FIG 11
`
`FIG 12
`
`

`

`Patent Application Publication
`
`Mar. 6, 2003 Sheet 9 of 9
`
`US 2003/0046099 A1
`
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`

`

`US 2003/0046099 A1
`
`Mar. 6, 2003
`
`SPATIALLY-BASED VALUATION OF PROPERTY
`
`FIELD OF THE INVENTION
`
`[0001] The present
`relates to a method and an
`invention
`for valuation of property.
`In particular, but not
`apparatus
`to a computer-imple-
`relates
`invention
`exclusively,
`the
`for providing
`mented method and a computer program
`a
`spatially-based valuation of property. Certain aspects of the
`to mass appraisal of
`relate more specifically
`invention
`property values.
`
`BACKGROUND OF THE INVENTION
`
`is an estimate of value based on
`[0002] Property Appraisal
`opinion, of an adequately described property of a specific
`and analysis of appropriate
`age, supported by presentation
`In the case of domestic property an inspection
`information.
`is undertaken whereby a series of criteria are assessed. The
`combined output of the assessed criteria allow the valuer to
`produce an appraisal or an estimate of value for the property.
`In addition, a professional valuer may apply his or her own
`the assess-
`knowledge
`about
`to further
`the locality
`refine
`ment.
`
`[0003] Mass appraisal, as a method of systematic statisti-
`cal assessment,
`the same criteria as single apprais-
`requires
`als. It therefore
`follows
`as outlined
`the same principles
`the two forms of assess-
`above, the main dilference between
`ment being multiplicity. As with single appraisals, mass
`judged by two core factors of
`appraisal models are primarily
`accuracy. There are various
`and predictive
`transparency
`tech-
`models or hybrid models and associated modelling
`available; many of these however might
`niques currently
`perform well in either one of the two factors of transparency
`and accuracy, but not both. This might be explained by
`the stratifi-
`issues such as the sample size, its distribution,
`the homogeneity of the area or other
`local
`cation used,
`factors.
`environmental
`It is commonly accepted that location of a property
`[0004]
`factor alfecting
`is the most important
`its value. Significant
`in value can occur over short distances, even
`dilferences
`within a single street. Property appraisers will infer a sub-
`stantial amount of information
`its
`from
`about a property
`location, which ability is based largely on local knowledge
`itself will exert an
`and experience.
`location
`In addition,
`influence on nearby properties.
`[0005] Modelling of property values,
`therefore,
`should
`take into account the significant elfect of location on prop-
`erty value. However, due to the difflculties of reproducing
`local knowledge of appraisers
`in a model, many valuation
`location when
`into account
`models do not directly
`take
`instead making use of 'pseudo-location'
`valuing properties,
`signifiers, such as local amenities, accessibility
`to services,
`and the like; however, such signifiers do not directly reflect
`influence of location, and so can be inaccurate.
`In
`the
`addition, such models typically will incorporate many such
`pseudo-location
`signifiers
`to minimise
`the
`in an attempt
`increases
`errors inherent
`this therefore
`in such an approach;
`time, and requires detailed assessment
`computer processing
`of local areas thereby
`the expense of generating
`increasing
`the models.
`
`[0006] Other more complex models do attempt
`to incor-
`porate location as a factor, all of which require an assess-
`
`ment of neighbourhoods
`or sub-markets. The housing mar-
`is a set of distinct but
`sub-markets,
`ket
`interrelated
`by one or several
`dwellings dilferentiated
`encompassing
`there is little consensus on
`alternative dimensions. However,
`should be defined according
`whether sub-markets
`to prop-
`erty characteristics, or based on the actual house price.
`[0007] Sub-markets may be defined in a number of ways.
`In a spatial context, it is possible to create localised regions
`the aggregation of units such as postal
`formed
`through
`zones, enumeration districts, or ward boundaries. The use of
`'political' or other non-property based locational areas cre-
`related to boundary positioning;
`ates problems
`that is, such
`boundaries have not been drawn up on the basis of property
`values, and so do not truly reflect the elfect of location on
`is based on quantitative
`property values. Another approach
`characteristics of the dwellings,
`type, size,
`such as house
`age, etc. ; or house prices may be used
`sub-
`to identify
`markets. These traditional models however assume homo-
`thus density over a unit area.
`in distribution
`and
`geneity
`this type of
`can be given using
`Further, no consideration
`to trends which occur across the bound-
`analytical method
`aries of these areal units. Clusters of value which may be
`than average for the whole unit may be 'lost' during
`higher
`analysis. Locational analysis
`is normally encompassed by
`is constant, or by
`that the locational value
`either assuming
`sub-dividing units into more readily definable areas such as
`retail, business or financial districts and assuming each to be
`constant. In many cases the locational value of these districts
`the valuers' expert knowledge
`may be accounted for through
`of the location.
`[0008] Although
`to incorporate
`these models do attempt
`the elfect of location on property values,
`the sub-markets
`of the actual
`thereby defined are often unrepresentative
`sub-markets, while no attempt is made to treat the elfects of
`location within a sub-market;
`that is, the models assume that
`the elfect of location within a sub-market
`is identical on
`the sub-market. This can lead
`to
`every property within
`the possibility of loca-
`inaccurate valuations,
`and ignores
`tional trends within a sub-market.
`In order to go some way
`towards overcoming
`these dilficulties, conventional models
`can only rely upon creating smaller and smaller sub-mar-
`kets, using more and more data, which will clearly increase
`time and use more computer memory.
`computer processing
`the problem of directly considering
`the elfects of
`In addition,
`location on property values remains unaddressed.
`the objects of embodiments
`[0009] It is among
`of the
`the elfects
`to provide a valuation model whereby
`invention
`of spatial
`location on property values may be directly
`into the model.
`incorporated
`the objects of certain embodi-
`[0010] It is further among
`ments of the invention
`to provide a computer-based model-
`and computer program which may generate
`ling method
`property valuations at a lower computer processing burden
`sacrificing
`valuation models, without
`than conventional
`accuracy.
`
`SUMMARY OF THE INVENTION
`
`[0011] In certain embodiments
`of the
`these
`invention,
`in part, by making use of statistical
`objects are achieved,
`property values at a
`techniques
`to interpolate
`unknown
`location from known property values of a particu-
`particular
`lar location. That is, X and Y co-ordinates
`(or any other
`
`

`

`US 2003/0046099 A1
`
`Mar. 6, 2003
`
`location defining variables) of all properties
`are known,
`together with values for some of the properties. Statistical
`techniques may then be used to calculate unknown property
`values on the basis of their spatial relationship
`to the known
`property values. Selected embodiments of the invention may
`factors
`incorporate
`the model
`additional
`to improve
`into
`accuracy of valuations.
`to a first aspect of the present invention,
`[0012] According
`method of spa-
`there is provided a computer-implemented
`valuation of a subject property,
`tially-based
`the method
`the steps of:
`comprising
`[0013] selecting a subset of properties
`for compari-
`son from a computer database containing character-
`istics of a plurality of properties of known value, the
`characteristics
`at least a location and a
`including
`value of each property,
`the database
`further
`and
`containing characteristics of a subject property of
`location;
`known
`[0014] generating an index of similarity matrix of the
`subset of properties;
`[0015]
`comparable
`spatially proximate
`identifying
`to the subject property, by means of a
`properties
`distance factor and an index of similarity
`threshold;
`and
`
`the value of the subject property
`[0016] calculating
`based on the values of the identified spatially proxi-
`mate comparable properties.
`[0017] Thus, the present
`invention allows the calculation
`of a property value based on its spatial location with respect
`to the identified comparable properties.
`[0018] The
`'index of similarity matrix',
`as used
`term
`herein, refers to a table or other data structure
`indicating
`the
`overall degree of similarity between each property and every
`for a selected dataset as a correlation coef-
`other property
`ficient for each pair of properties,
`the coel5cient being
`derived from all selected attributes of the properties. Note
`statistical
`the usage herein dilfers
`from
`the known
`that
`'index of similarity'
`function, with the term as used herein
`to the scoring range from the correlation.
`referring
`[0019] The term 'spatially proximate' as used herein refers
`distance
`lie within
`a predetermined
`to properties which
`threshold or factor from a particular property.
`the calculation of the value of the sub-
`[0020] Preferably
`ject property may be weighted with regard to the proximity
`of the comparable properties. That is, the value of properties
`the subject property
`which are immediately
`adjacent
`are
`to have a larger elfect on the value of the subject
`likely
`away. Weighting of the
`than properties
`farther
`property
`calculated value accordingly may thus be used to account for
`location of a property
`in a manner which varies continuously
`the area chosen, rather
`the area as
`throughout
`than treating
`a single, homogenous
`region.
`[0021] There may of course be a plurality of subject
`the database. The step of subset
`included
`properties
`in
`the step of selecting
`selection may
`then also
`include
`a
`particular subject property or properties.
`[0022] The calculation of the value of the subject property
`may make use of an
`interpolation
`is, a
`technique;
`that
`the value of unknown points
`interpolates
`technique which
`
`from the value of known points. Most preferably,
`the cal-
`culation makes use of Kriging
`(also known
`interpolation
`the skilled person will be aware of
`simply as 'Kriging');
`for performing Kriging. In general, Kriging may
`techniques
`be used to calibrate
`to refine a calculated
`the method and/or
`value, while the basic calculation of the value will be made
`the index of similarity matrix of comparable proper-
`using
`ties, as described above. Alternative calculation
`techniques
`may be used if desired; however, it is believed at present that
`Kriging olfers the best method for calculating
`the value
`in
`terms of computational
`burden and accuracy of calculated
`values. For example, spline or inverse distance weighted
`functions may be used.
`interpolation
`the location of the properties is recorded
`[0023] Preferably
`as X and Y co-ordinates. This is a
`the database
`within
`convenient format to use, and may use for example, national
`references or latitude and longitude measure-
`grid mapping
`ments as X and Y co-ordinates. Conversion of latitude and
`into a more con-
`from sexagesimal
`longitude measurements
`venient format (for example, decimal representation) may be
`used. Other location formats may also be used, for example,
`polar co-ordinates.
`[0024] The value of the properties may be represented as
`absolute price, relative price, or price per square meter or
`square foot.
`
`includes characteristics of
`[0025] Preferably
`the database
`in addition to location and value. Ideally, these
`the properties
`characteristics will be those which are believed
`to have an
`the value of a property;
`age of
`elfect on
`for example,
`type of building,
`size, number of bathrooms,
`building,
`central heating, garage, and so forth. Additional character-
`istics which do not alfect property value may also be
`if desired.
`included,
`[0026] Selection of the subset of properties may be carried
`for example by a computing
`device
`out automatically,
`characteristics
`according to predetermined
`(such as within a
`area), or manually
`by an operator. Where a
`predefined
`manual selection
`this may be by area (such as a
`is made,
`town, or a district), or by non-spatial
`characteristics
`(for
`all detached houses), or by a combination of
`example,
`spatial and non-spatial characteristics. Reference herein to ' a
`subset' of properties may of course be taken
`to include
`selection of all properties on the database.
`[0027] The database may be local to the computer
`imple-
`the present method, or may be remote
`therefrom
`menting
`and accessed by for example a telecommunications
`network.
`index of similarity
`[0028] The step of generating
`the
`score for each
`matrix comprises calculating
`a similarity
`(both of known and unknown value) when com-
`property
`the subset. The
`pared with every other property within
`is given as a correlation coel5-
`similarity score preferably
`cient for the set of characteristics of each property; conven-
`techniques may be used to calculate
`tional statistical
`this
`correlation coel5cient. The index of similarity matrix may
`be calculated using all characteristics
`included within
`the
`database, or only a subset thereof. If a subset of character-
`the step of
`istics is used, the method may further comprise
`the characteristics
`to be compared.
`selecting
`
`[0029] Where characteristics
`include non-
`to be compared
`'house type'
`numerically coded characteristics (for example,
`'terrace', and so
`'detached',
`may be coded as 'bungalow',
`
`

`

`US 2003/0046099 A1
`
`Mar. 6, 2003
`
`the further step of auto-
`forth), the method may comprise
`characteristics
`non-numerical
`matically
`into
`recoding
`'house type' may be
`numerical characteristics (for example,
`recoded as 1, 2, 3, etc. ). This allows such characteristics
`to
`index of similarity matrix. The
`be included within
`the
`numerical codes assigned may be arbitrary, provided
`that
`the same numerical code.
`like properties will be assigned
`
`[0030] Generation of the matrix preferably
`further com-
`prises the step of standardising
`to be com-
`characteristics
`that each characteristic may be meaningfully
`pared, such
`compared with each other characteristic. For example, while
`the value of a property may range from, say, $10, 000 to
`$100, 000, the number of bedrooms may range only from 1
`to 5. Standardisation of these characteristics
`allows mean-
`index of
`to be made. The calculated
`ingful comparisons
`to provide a similarity
`similarity may further be normalised,
`score of between 0 and 1 for each property.
`
`[0031] During
`identification of spatially proximate
`the
`comparable properties step, the distance factor and index of
`set by an operator, or
`threshold may be manually
`similarity
`may be predetermined
`by a computer
`the
`implementing
`method. Alternatively,
`the method may further comprise
`the
`step of calculating optimal values for either or both of these
`values based on the database. For example,
`the optimal
`distance factor for accurate valuation of properties will vary
`the precise contents of the database;
`on
`the
`depending
`this optimal factor based on the
`method may thus calculate
`factor may,
`to be used. The optimal distance
`for
`data
`example, be generated by a semi-variogram model with the
`the distance of influence
`(spatial auto-
`range determining
`correlation). The index of similarity
`threshold value may be
`by, for example,
`selecting values
`generated
`in
`the
`top
`percentile from the similarity matrix. The optimal value may
`or may be simply suggested
`be used automatically,
`to an
`operator.
`
`the step of
`[0032] The method may
`comprise
`further
`the location of properties and/or other character-
`displaying
`istics on a display. The display may further comprise a map
`of a relevant area; for example, a town street map may be
`overlaid with the location of each property
`in the database.
`
`the step of
`[0033] The method may
`comprise
`further
`the calculated value of the subject property
`to an
`reporting
`operator. A report may be given by any convenient output
`device; for example, on a display monitor, via a printer, by
`generated speech, by SMS or other messaging service trans-
`and so forth.
`mitted over a telecommunications
`network,
`the step of reporting
`The method may yet further comprise
`details of the calculation:
`for
`additional
`to an operator
`example, details of the identified comparable properties may
`be given, or an estimated
`rating. This allows an
`reliability
`operator to determine on what basis the valuation has been
`made, so rendering
`relatively
`to a
`the method
`transparent
`user.
`
`the step of
`[0034] The method may
`comprise
`further
`for calculated value of a
`calculating
`a reliability
`rating
`statistical techniques may be
`subject property. Conventional
`used to provide a reliability
`rating based on the database
`used.
`
`the step of
`[0035] The method may yet further comprise
`removing properties with statistically outlying characteris-
`tics from the subset of properties. For example, if a database
`
`includes details of one particular property which sold for a
`significant amount above or below its actual value, then this
`outlier may skew the calculated values of subject properties.
`Removal of such properties
`the accuracy of the
`improves
`method. Outliers may be identified automatically, or manu-
`ally. Certain embodiments of the invention may allow for
`to have their characteristics edited and returned
`to
`outliers
`the subset of properties,
`for
`removed;
`rather
`than simply
`example, if a user identifies an outlier due to an incorrectly-
`to correct it rather
`they may edit the value
`entered value,
`than excluding
`from the database altogether.
`the property
`
`to a second aspect of the present
`[0036] According
`inven-
`is provided
`for
`a computer program product
`there
`tion,
`valuation of a subject property comprising
`spatially-based
`code recorded on a data carrier,
`the
`computer program
`computer program code comprising:
`
`the selection of a subset of
`[0037] code for allowing
`properties for comparison
`from a computer database
`containing characteristics of a plurality of properties
`of known value, the characteristics
`including at least
`a location and a value of each property,
`the
`and
`further containing characteristics of a sub-
`database
`ject property of known
`location;
`
`index of similarity
`[0038] code for generating
`an
`matrix of the subset of properties;
`
`[0039] code for identifying
`spatially proximate com-
`to the subject property, by means
`parable properties
`of a distance factor and an index of similarity
`thresh-
`old; and
`
`the value of the subject
`[0040] code for calculating
`property based on the values of the identified spa-
`tially proximate comparable properties.
`
`[0041] The data carrier may be in the form of magnetic
`tape, optical discs such as CD-ROMs, magnetic media such
`as floppy discs or hard discs, or permanent data carriers such
`as ROM chips and the like. The data carrier may still further
`comprise optical or electrical signal carriers such as optical
`cables.
`fibres or communications
`
`[0042] The computer program product may further com-
`prise code for removal of outliers from the subset of prop-
`erties.
`
`[0043] The computer program product may further com-
`prise code for recording calculated property values
`in a
`database.
`
`to a still further aspect of the present
`[0044] According
`there is provided a computer program
`for spa-
`invention,
`tially-based valuation of a subject property,
`the computer
`program comprising:
`
`the selection of a subset of
`[0045] code for allowing
`properties for comparison
`from a computer database
`containing characteristics of a plurality of properties
`of known value, the characteristics
`including at least
`a location and a value of each property,
`the
`and
`further containing characteristics of a sub-
`database
`ject property of known
`location;
`
`index of similarity
`[0046] code for generating
`an
`matrix of the subset of properties;
`
`

`

`US 2003/0046099 A1
`
`Mar. 6, 2003
`
`spatially proximate com-
`[0047] code for identifying
`to the subject property, by means
`parable properties
`of a distance factor and an index of similarity
`thresh-
`old; and
`
`to a yet further aspect of the present
`[0061] According
`there is provided a method of providing
`a spa-
`invention,
`to a customer,
`tially-based property valuation
`the method
`the steps of:
`comprising
`
`the value of the subject
`[0048] code for calculating
`property based on the values of the identified spa-
`tially proximate comparable properties.
`
`to a still further aspect of the present
`[0049] According
`there is provided a computer system for spatially-
`invention,
`based valuation of a subject property,
`the system compris-
`ing:
`
`[0050] means for selecting a subset of properties
`for
`comparison
`from a computer database containing
`characteristics of a plurality of properties of known
`value, the characteristics
`including at least a location
`and a value of each property, and the database further
`containing characteristics of a subject property of
`location;
`known
`
`[0051] means for generating
`an index of similarity
`matrix of the subset of properties;
`
`[0052] means
`for
`proximate
`identifying
`spatially
`to the subject property, by
`comparable properties
`means of a distance factor and an index of similarity
`threshold; and
`
`the value of the subject
`[0053] means for calculating
`property based on the values of the identified spa-
`tially proximate comparable properties.
`
`[0054] The system may
`comprise means
`further
`remotely accessing said computer database.
`
`for
`
`[0055] The system may still further comprise means for
`generating a report of the value of the subject property
`to a
`user. The report generation means may comprise a display
`means, such as a computer monitor or the like, printing
`means, sound generating means, or means for accessing a
`remote communications network, for example the internet, a
`network, or the like.
`telecommunications
`to a yet further aspect of the present
`[0056] According
`a method of spatially-based
`is provided
`there
`invention,
`valuation of a subject property,
`the method comprising
`the
`steps of:
`
`[0057] selecting a subset of properties
`for compari-
`son from a database containing characteristics of a
`plurality of properties of known value,
`the charac-
`teristics including at least a location and a value of
`each property, and the database
`further containing
`characteristics of a subject property of known
`loca-
`tion;
`
`[0058] generating an index of similarity matrix of the
`subset of properties;
`
`[0059]
`comparable
`spatially proximate
`identifying
`to the subject property, by means of a
`properties
`distance factor and an index of similarity
`threshold;
`and
`
`the value of the subject property
`[0060] calculating
`based on the values of the identified spatially proxi-
`mate comparable properties.
`
`[0062] selecting a subset of properties
`for compari-
`son from a computer database containing character-
`istics of a plurality of properties of known value, the
`characteristics
`at least a location and a
`including
`value of each property,
`the database
`further
`and
`characteristics of a subject property of
`containing
`location;
`known
`
`[0063] generating an index of similarity matrix of the
`subset of properties;
`
`[0064]
`comparable
`spatially proximate
`identifying
`to the subject property, by means of a
`properties
`distance factor and an index of similarity
`threshold;
`
`the value of the subject property
`[0065] calculating
`based on the values of the identified spatially proxi-
`mate comparable properties;
`
`[0066] providing
`the calculated
`a report containing
`value of the subject property
`to a customer; and
`
`[0067] charging
`the report.
`
`the customer
`
`in return for providing
`
`[0068] The report may be provided by any convenient
`means, for example, on paper, by email or other communi-
`cations network, on a computer or other display screen,
`(PDA) or