Abstract:
This present invention relates to a lamp drive apparatus and a drive method for an LCD equipped portable electronics to maintain a user-selected level of brightness in accordance with surrounding temperature of the lamp. In one operation mode a lamp drive apparatus reduces the current, which is applied into the lamp to maintain the already selected level of brightness in accordance with a detected lamp surrounding temperature where the brightness of the lamp has already been set in the LCD, to make the LCD device to illuminate no brighter than the selected level of brightness. Accordingly, the battery power can be used more efficiently or effectively. Thus, the battery life can be extended.

Description:
FIELD OF THE INVENTION 
   The present invention relates to a system for analysing textual data. In particular, the analysis results in revealing information hidden in textual data. Such a system can be used in a method for developing consumer products, or for better targeting the marketing consumer products, when the textual data that is to be analysed is obtained from consumers. 
   BACKGROUND OF THE INVENTION 
   Developing and marketing new (consumer) goods, and in particular goods in the fast moving consumer goods area, involves in many cases at some stage obtaining information from consumers as to what sort of products they want, and/or obtaining information from consumers to effectively target marketing and sales, and/or research during the product development process, and/or monitoring the consumer appraisal once the product is/has been evaluated before or after being launched. Gathering such information can be done in many different ways, e.g. by interviewing individuals or groups of consumers, feedback after purchase, spontaneous email (e.g. from consumers to care-lines of product websites), questionnaires call for free-text answers, et cetera. Usually such information is obtained in a textual format or can be translated into that. 
   Whether the information appears directly expressed or implicit in the text, it may be desired to perform some analysis or information extraction and/or interpretation to obtain this information. Existing examples of information extraction from factual documents (e.g. reports, scientific prose, news feeds, legal texts, etc.) are based on the recognition of entities and events. In order to fill pre-defined templates, the linguistic elements which represent the entities need recognising, the syntactic-structures in which the entities are embedded need disentangling, and the nature of the semantic links between entities need interpreting. 
   Although in principle similar information extraction techniques could be attempted with unstructured subjective textual data, the infinite multiplicity of the modes of expression used by individuals on subjects such as personal issues, opinions, beliefs and habits does not make these methods wholly appropriate and does not give satisfactory results. Examples of subjective or unstructured text are literature, free-text questionnaire answers, interviews and loosely-directed monologues, focus-groups interactions, spontaneous communications, etc. The information which is to be revealed are not events or entities, but rather qualifiers, concepts, opinions, etc. as well as the characteristics of a specific linguistic expression. 
   There are also techniques known for analysing textual data which can be grouped under the header linguistic analysis techniques. Examples of such techniques are extraction of linguistic units or linguistic features from textual chains, analysis of lexical semantic patterns, analysis of collocations and coherent groups, analysis of co-occurrences and conceptual chains, analysis of affect, and others. Such techniques are discussed in:
         Atkins, B.T.S. &amp; Zampolli, A. (eds) (1994). Computational approaches to the lexicon. Oxford: Oxford University Press.   Firth, J.R. (1951). Modes of meaning (Essays and Studies). In J.R. Firth: Papers in Linguistics, 190–215, London: Oxford University Press.   Ghiglione, R., Landré, A., Bromberg, M., Molette, P. (1998). L&#39;analyse automatique des contenus. Paris: Dunod.   Lebart L., Salem A., Berry L. (1998). Exploring textual data. Dordrecht: Kluwer Academic Publishers.   Marchand, P. (1998). L&#39;analyse du discours assistée par ordinateur. Concepts, méthodes, outils. Paris: Armand Colin (U).   Roberts, C.W. (1997). Text analysis for the social sciences: methods for drawing statistical interferences from texts and transcripts. Lawrence Erlbaum Assoc. Publishers, Mahwah, N.J.   Sinclair, J.M. (1991). Corpus, concordance, collocation. Oxford: Oxford University Press.   Whissell, C., Fournier, M., Pelland, R., Weir, D. &amp; Makarec, K. (1986). A dictionary of affect in language: IV. Reliability, validity, and applications. Perceptual and Motor Skills.       

   While such information extraction or linguistic analysis techniques may provide valuable information, there is more information which is hidden in textual data which is not revealed by these methods. 
   A wide variety of statistical methods are available for extracting information from numerical data. Such statistical methods can be anything from simple counting to more advanced statistical techniques, e.g. dimension reduction, clustering, hypothesis testing, model fitting, correlation and others. Various such statistical techniques are described in:
         Dimension reduction: Krzanowski W.J. &amp; Marriot F.H.C. (1994) Multivariate Analysis—Edward Arnold.   Clustering: Everitt B.S. (1993) Cluster Analysis—Edward Arnold.   Hypothesis testing: Altman D.G. (1991) Practical Statistics for Medical Research—Chapman &amp; Hall.   Model fitting: e.g. Draper N.R. &amp; Smith H. Applied Regression Analysis—Wiley (1998)   Correlation: The Cambridge Dictionary of Statistics (1998), Everitt B.S.—Cambridge University Press.   Time Series: The Analysis of Time Series: An Introduction. Chatfield C. (1996).       

   While such statistical methods may provide information from numerical data, they are not directly applicable to textual data. 
   New profiling and segmentations of the consumer population are being sought, which are no longer based on demographics but on new drivers like life style, educational attainment, attitudes to the environment, health issues, social preferences, etc. 
   SUMMARY OF THE INVENTION 
   Hence, there was a need for a tool or system that can be used to analyse unstructured, subjective or personal text. 
   It has now been found that the above may be achieved (at least in part) by a system for revealing information by subjecting textual data to: 
   a) a module for entering textual data 
   b) a module (A) for linguistic analysis for analysing said data, 
   c) a module (B) for statistical analysis of the results of module (A). 
   Preferably the system of the invention is an electronic system for example a computer system 
   In this, the statistical analysis is understood not to relate just to simple counting and calculating averages and percentages. It will be clear to the person of average skill what statistical analysis is and what is to be understood as linguistic analysis. There are also examples of linguistic analysis tools that have some basic statistical analysis incorporated therein, and some statistical tools which have a minimum of linguistic analysis embedded in them. For example, word frequency counts which define a word as a string of characters comprised between two successive spaces (system with minimal linguistic analysis); for example, customised text editors which manage manually-defined labels indexing the semantic contents of portions of documents and return findings on the relative importance of certain themes across a number of texts (system with minimal statistical analysis). For the purpose of this invention, these will still be called linguistic tools, and statistical tools, respectively, i.e. independent of the presence of a bit of the other technique in them. 
   RU 2107950 XP 002181209 (Epodoc) discloses the use of acoustic and linguistic analysis and statistic criteria for decision making. This document does not indicate the advantages of first applying a linguistic analysis and subsequently applying a statistical analysis on the results thereof. 

   DETAILED DESCRIPTION OF THE INVENTION 
   It has now been found that statistical analyses may be performed on data that is obtained from a preceding linguistic analysis of textual data, and that such a combination of techniques yields information from unstructured, subjective or personal texts not available so far. 
   In order to practice this invention it is preferred if such techniques are present as modules in a system, especially because there is a wide range of both linguistic and statistical techniques to choose from. Of course, such a system will contain some form of module to enter the textual data to be analysed. A system according to the invention may also comprise a module to present the output, but it may also be possible that the module that provides the statistical analysis provides the output itself. 
   In the system according to the invention, the linguistic analysis is preferably achieved by subjecting the textual data to one or more of: 
   a) extraction of linguistic units or linguistic features from textual chains 
   b) removal of stop-words [list re-ordered] 
   c) analysis of lexical semantic patterns 
   d) analysis of collocations and coherent groups 
   e) analysis of co-occurrences and conceptual chains 
   f) analysis of lexical complexity, co-reference 
   g) analysis of affect 
   h) tagging units in the textual chain yields: Part-Of-Speech tags, semantic descriptors, other indexing tags, syntactic tagging, functional tagging 
   i) analysis of syntactic complexity 
   If one or more of the techniques c) to i) is chosen, it is preferably applied after a preliminary extraction of linguistic units or linguistic features from textual chains (a) and/or the removal of stop words (b). The extraction of linguistic units or linguistic features is preferably done in such as way that it yields one or more of: 
   A1 letters 
   A2 morphemes
         A2′ free morphemes   A2″ bound morphemes       

   A3 words (e.g. simple, compound), lemmas &amp; word classes (POS)
         A3′ nouns (e.g. common nouns, proper names)   A3″ verbs (including auxiliaries)   A3′″ adjectives   A3′4 determiners (e.g. articles, possessive adjectives, demonstrative adjectives, exclamative adjectives, quantifiers and numerals)   A3′5 pronouns and pro-forms   A3′6 adverbs (e.g. adjuncts and subjuncts, disjuncts, connectors)   A3′7 exclamations and interjections   A3′8 prepositions   A3′9 conjunctions       A4 phrases and idioms (e.g. noun phrases, verb phrases, adjectival phrases, prepositional phrases, adverbial phrases)   A5 clauses (e.g. relative clauses, nominal clauses, adverbial clauses, independent, comment clauses)   A6 sentences   A7 paragraphs   A8 discourse structures, rhetorical structures   A9 functions (e.g. subject, object, complement, adverbial)   A10 semantic patterns (e.g. Key Words In Context&#39;s), collocations, co-occurrences, semantic fields, semantic networks, semantic components)   A11 lexical patterns, lexical complexity, co-reference   A12 syntactic patterns, syntactic complexity.   

   In the system according to the invention the statistical analysis is preferably achieved by subjecting the results of module (A) to one or more of:
         Dimension reduction   Clustering   Hypothesis testing   Model fitting   Correlation       

   These statistical techniques are known as such. 
   It has been found that it may be preferred to analyse texts by a combination of techniques according to the invention in which the linguistic analysis is the extraction of linguistic units or linguistic features and the statistical analysis is dimension reduction. Alternatively, it may be preferred to combine the extraction of linguistic units or linguistic features (as linguistic analysis) with clustering as statistical analysis. Another preferred combination is wherein the linguistic analysis is the analysis of co-occurrences and collocations and the statistical analysis in hypothesis testing. 
   The system according to the present invention is in particular suitable for textual data which are captured from one or more of:
         a) interviews   b) focus groups   c) syndicate groups   d) questionnaires (free text)   e) computer mediated communication (e.g. chat room conversations, email, computer conferencing)   f) telephone conversations   g) video conferences   h) audio and audiovisual broadcasts   i) encoded language (e.g. morse) as well as published or unpublished print or electronic media, including:   j) newspapers   k) books   l) magazines   m) electronically published media   n) naturally occurring conversations   o) mixtures of the above       

   Although the origin of the text may be anything as set out above (and even other), the physical format of such textual data to be analysed is one or more of:
         a) transcripts of speech   b) electronic text   c) printed or handwritten media   d) transliterations.       

   The system according to the invention may have any suitable physical form. Given the amount of information to be processed the module for entering textual data preferably comprises means for getting the textual data into an electronically readable format and has optionally further one or more of the following functionalities: concatenating or splitting files by respondent or by question, creating tagged or lemmatised sentences, all manner of string/line/tagged sequences searching and replacement, multi-criteria retrieval. The information may be stored using electronic storage means, e.g. in the form of databases, computer readable data carriers or other. 
   The system according to the present invention may further contain a module for linguistic post processing after module (B). In that case, such linguistic post-processing comprises preferably one or more of
         the grouping of concepts,   the averaging out of semantic values,   the building of word nets from results.       

   The output, either with or without linguistic post processing, may be generated in any suitable form. Examples are graphs, tables, lists, computer-screen projections, networks, webs, trees, dynamic lay out graphs, hard copies thereof. 
   As set out herein before, the invention provides a system for analysing textual data. Although analysing single sets of textual data can be desired for some purposes, it may provide further insight in information if two or more different sets of textual data are analysed using a system according to the present invention and the two or more outputs may subsequently be compared. Likewise, it may be preferred to compare the revealed information obtained using a system according to the invention with existing numerical or textual data. For example, when using the system according to the invention for improving the development of consumer products, such existing numerical or textual data may comprise or relate to one or more of physical and/or chemical properties of products and/or packaging, physical measurements, demographic information, quantitative questionnaire results, sensory panel results, consumer behaviour, time/date information. 
   Although the system according to the present invention may be used for analysing existing textual data, the system can also be adapted such that the textual data to be analysed are captured and analysed in real time. For specific purposes, it may also be preferred to feed back the obtained output using the system according to the invention to the individuals who produced the original textual data. 
   EXAMPLES 
   Example 1 
   Table 1 shows the snow reports taken from the BBC online website (http://www.bbc.co.uk/weather/sports/features/skiing_text.shtml) on the 6 th  March 2001. The description for Scotland was excluded from the analysis as both the presentation and information contained within the report were judged to be very different to those used for the other countries. 
   
     
       
             
           
             
             
           
         
             
               TABLE 1 
             
             
                 
             
             
               Snow reports taken from the BBC online website 
             
             
               (http://www.bbc.co.uk/weather/sports/features/skiing_text.shtml) 
             
             
               on Mar. 6, 2001. 
             
             
                 
             
           
           
             
                 
             
           
        
         
             
               AUSTRIA 
               The temperature in Austria has risen over the 
             
             
                 
               weekend and this is effecting the lower slopes of some 
             
             
                 
               of the resorts. Kitzbuhel&#39;s (25 cm/115 cm) runs to 
             
             
                 
               resort are slushy and worn although the upper area is 
             
             
                 
               still offering some good skiing. Rain on Sunday in Soll 
             
             
                 
               (50 cm/150 cm) has made the snow a bit wet and 
             
             
                 
               heavy, especially on the lower runs. There is some 
             
             
                 
               excellent skiing still to be found in Austria with St 
             
             
                 
               Anton (75 cm/320 cm) offering powder off piste and 
             
             
                 
               Obergurgl (60 cm/240 cm) giving great piste 
             
             
                 
               skiing/boarding opportunities. 
             
             
               FRANCE 
               Many off the French resorts had high 
             
             
                 
               temperatures over the weekend giving slushy or heavy 
             
             
                 
               snow. The avalanche risk in many resorts has also 
             
             
                 
               increased to ‘high’ or above. Snow was falling on the 
             
             
                 
               slopes of Flaine (60 cm/320 cm) over the weekend but 
             
             
                 
               this turned to sleet and rain at resort level. La Plagne 
             
             
                 
               (115 cm/215 cm) also had snow but it was very wet 
             
             
                 
               and the lower slopes are described as ‘slushy’. Les 
             
             
                 
               Arcs (85 cm/260 cm) and Alpe D&#39;Huez (78 cm/220 
             
             
                 
               cm) are also in a similar state, offering good skiing in 
             
             
                 
               the upper areas but with wet snow lower down. 
             
             
               SWITZERLAND 
               Along with the rest of Europe 
             
             
                 
               Switzerland experienced warm temperatures over the 
             
             
                 
               weekend. The snow is still in pretty good condition in 
             
             
                 
               most the resorts and temperatures are falling today. 
             
             
                 
               Verbier (70 cm/180 cm) was unable to open many of 
             
             
                 
               its lifts on Sunday due to bad weather but once this 
             
             
                 
               clears the resort will be offering good skiing 
             
             
                 
               throughout. Davos (95 cm/180 cm) had its full uplift 
             
             
                 
               open during the weekend and it&#39;s pistes are in great 
             
             
                 
               condition. 
             
             
               ITALY 
               Italy had some snow over the weekend and 
             
             
                 
               conditions on the whole remain good. Cervinia (120 
             
             
                 
               cm/300 cm) had 20 cms of snow over the weekend 
             
             
                 
               and the conditions both on and off piste are excellent. 
             
             
                 
               Madonna di Campiglio (85 cm/240 cm) unfortunately 
             
             
                 
               had rain below 1750 m and this has made the lower 
             
             
                 
               slopes quite wet, but there is still good skiing above 
             
             
                 
               this height. 
             
             
               ANDORRA 
               Rain over the weekend has left most the 
             
             
                 
               resorts with wet and slushy slopes. Soldeu (50 
             
             
                 
               cm/110 cm) also suffered from high winds yesterday 
             
             
                 
               only allowing it to open 8 lifts. Today it is sunny but 
             
             
                 
               more snow is needed to repair the damaged slopes. 
             
             
               NORWAY/ 
               Some strong winds and snowfall over the weekend 
             
             
               SWEDEN 
               have given variable conditions in this area. 
             
             
                 
               Geilo (115 cm/130 cm) had blizzard conditions on 
             
             
                 
               Sunday but the skiing should be great once the storm 
             
             
                 
               finishes. Temperatures on the whole have risen but are 
             
             
                 
               still below zero. 
             
             
               GERMANY 
               Some of the German resorts received 
             
             
                 
               snow over the weekend and this has improved 
             
             
                 
               conditions. Oberstdorf (20 cm/235 cm) has all its lifts 
             
             
                 
               open and snow is falling there today. Reit im Winkl 
             
             
                 
               (50 cm/180 cm) also has all lifts open and is offering 
             
             
                 
               great skiing. Snow is expected for most of Germany 
             
             
                 
               this week. 
             
             
               BULGARIA 
               Bulgaria has had warm temperatures and 
             
             
                 
               what snow there was is suffering. Borovets 
             
             
                 
               (20 cm/50 cm) has rocks showing through on some of 
             
             
                 
               it&#39;s pistes. All the resorts need snow very soon, at 
             
             
                 
               present there doesn&#39;t seem to be any on the way. 
             
             
               SCOTLAND 
               The Foot and Mouth situation is being 
             
             
                 
               monitored by all the Scottish resorts at present and all 
             
             
                 
               are discouraging skiers, boarders, ski tourers, hill 
             
             
                 
               walkers and climbers not to leave the ski area boun- 
             
             
                 
               dries. Nevis Range, as of Feb. 03, 2001 has stopped 
             
             
                 
               climbers and hill walkers from accessing Aonach Mor. 
             
             
                 
               NEVIS RANGE—There are 6 lifts open today in the 
             
             
                 
               Nevis Range today and the skiing is good in all areas. 
             
             
                 
               There have been moderate amounts of fresh snow but 
             
             
                 
               due to a slight thaw the lower slopes have wet snow. 
             
             
                 
               CAIRNGORM—Unfortunately due to blizzard 
             
             
                 
               conditions there are only 2 lifts open today. Fresh 
             
             
                 
               snow is falling and when the storm stops conditions 
             
             
                 
               should be excellent. 
             
             
                 
               GLENCOE—All lifts are open and the conditions are 
             
             
                 
               very good. There are some icy patches but these are 
             
             
                 
               few and far between. The cover on the whole is fresh 
             
             
                 
               snow on a hard base. 
             
             
                 
               GLENSHEE—The majority of the uplift is operational 
             
             
                 
               today and the slopes have a complete cover of 
             
             
                 
               groomed, firm packed snow. The resort is reading 
             
             
                 
               itself for the Braemar Telemark Festival starting on 
             
             
                 
               Sep. 03, 2001. 
             
             
                 
               THE LECHT—All the main runs are complete with 
             
             
                 
               new snow on a firm base, there is also ample nursery 
             
             
                 
               area open. The skiing is very good throughout resort, 
             
             
                 
               with the Buzzard and Eagle runs offering some of the 
             
             
                 
               best snow. 
             
             
               AMERICA 
               Conditions throughout America are still very 
             
             
                 
               good and some resorts received a small top-up of the 
             
             
                 
               white stuff this weekend. Mammoth (240 cm/270 cm) 
             
             
                 
               has excellent conditions both on and off piste. 
             
             
                 
               Arapahoe Basin (130 cm/135 cm) has great powder off 
             
             
                 
               piste and lovely groomed slopes, but with minus 16° 
             
             
                 
               Celsius, the resort is a bit chilly. Beaver Creek 
             
             
                 
               (142 cm/144 cm) has all its lifts open and the 
             
             
                 
               skiing/boarding is great. 
             
             
               CANADA 
               There has been very little change to the 
             
             
                 
               Canadian resorts over the weekend. Most resorts are 
             
             
                 
               still offering good skiing. Red Mountain&#39;s 
             
             
                 
               (74 cm/126 cm) slopes are in great condition but more 
             
             
                 
               snow is needed to fully open up the off piste. Jasper 
             
             
                 
               (63 cm/155 cm) has some good off piste and all its lifts 
             
             
                 
               open. In general although conditions are good in most 
             
             
                 
               resorts more snow would be welcomed by all of them. 
             
             
                 
             
           
        
       
     
   
   These data from table 1 were separated into linguistic units of words (groups of characters separated by white spaces or punctuation) and stop words were removed using a standard list (which in this case was taken from the webpage: http://www-fog.bio.unipd.it/waishelp/stoplist.html). 
   These were formed into a words-country frequency matrix showing the number of times each word was used in describing the conditions present within each country. A subset of this matrix (as an example, whole matrix is too big to display) is shown in Table 2. 
   
     
       
             
           
             
             
           
             
             
             
             
             
             
           
         
             
               TABLE 2 
             
           
           
             
                 
             
             
               Submatrix of the Words-Country frequency matrix. 
             
           
        
         
             
                 
               Country 
             
           
        
         
             
               word 
               America 
               Andorra 
               Austria 
               Bulgaria 
               Canada 
             
             
                 
             
             
               AREA 
               0 
               0 
               1 
               0 
               0 
             
             
               BIT 
               1 
               0 
               1 
               0 
               0 
             
             
               BOARDING 
               1 
               0 
               1 
               0 
               0 
             
             
               CONDITION 
               0 
               0 
               0 
               0 
               1 
             
             
               CONDITIONS 
               2 
               0 
               0 
               0 
               1 
             
             
               EXCELLENT 
               1 
               0 
               1 
               0 
               0 
             
             
               FALLING 
               0 
               0 
               0 
               0 
               0 
             
             
               GOOD 
               1 
               0 
               1 
               0 
               3 
             
             
               GREAT 
               2 
               0 
               1 
               0 
               1 
             
             
               HEAVY 
               0 
               0 
               1 
               0 
               0 
             
             
                 
             
           
        
       
     
   
   The dimension reduction technique, correspondence analysis (as described in Greenacre (1984) Theory and Applications Of Correspondence Analysis, London: Academic Press) was then applied to this frequency matrix and the scores for the first two dimensions extracted for both the countries and words. 
     FIG. 1  shows a plot of the scores of the words and countries on the first two dimensions. Countries who are experiencing similar conditions and who have similar language used to describe their conditions will have similar scores from the correspondence analysis and so will be plotted close together in this map. The words strongly associated with the conditions present in a particular country or group of countries will also be plotted close to these countries. For example France and Andorra are plotted close to each other on the correspondence analysis map suggesting that the conditions in both of these countries are similar. Similarly Germany and Canada are grouped together. The conditions in France and Andorra are characterised by words such as “wet” and “slushy”, whilist the conditions in America are characterised by words such as “powder”, “excellent” and “great”. The position of Bulgaria on the map suggest that it is experiencing very different conditions from the other countries, this difference in conditions being characterised by the word “warm”. 
   These results can also be related to other sources of data. For example, the snow reports also contains measures of the depth of snow. If we take an average of these values for each country as a measure of the average depth of snow present in resorts in that country then we can relate this data to the output from the textual analysis.  FIG. 2  shows a clear statistically significant correlation (p=0.724, n=10, p=0.018) between the first dimension from the correspondence analysis and the average snow depth. This suggests that the differences in the language used to describe the snow conditions in different countries extracted by on the first correspondence analysis dimension is strongly related to the depth of snow present in the different countries. 
   The results from the correspondence analysis may alternatively be related to other measures such as temperature or altitude. If a series of reports were collected over time, time series modelling techniques may be used. Alternatively, given other relevant information, model building approaches to develop predictive models may be used, for example to be able to model visitor satisfaction or resort income with the resort as a function of the language used in the snow condition reports. 
   Example 2 
   An alternative embodiment is illustrated below using the same data set as in Example 1 (table 1). The data is subjected to the same linguistic analysis as in the previous embodiment. Distances between countries were then calculated using Jaccard coefficients, i.e. for each pair of countries the fraction of the words used in the description of conditions for either country which were used in the description of the conditions in both companies were calculated. This gave a similarity matrix shown in table 3: each pair of countries has a measure of similarity between 0 and 1, where a similarity of 0 would mean that the reports from the two countries have no words in common and a similarity of 1 would mean that the sets of words used in the reports for the two countries were identical. This was then subjected to a cluster analysis using Ward&#39;s method (SAS/STAT User&#39;s Guide, 1990). Choosing a four cluster solution gave us clusters of countries {America, Canada, Germany, Switzerland}, {Andorra, Austria, France, Italy}, {Norway} and {Bulgaria}. 
   These clusters identify countries experiencing similar snow conditions reflected in the use of similar language in their snow reports. An idea of the conditions represented by each of these clusters can be obtained by observing the words used in the descriptions of the conditions of the countries in the cluster which are used infrequently elsewhere. For example, the words “lift”, “great” and “open” are used in all of the reports in the countries {America, Canada, Germany, Switzerland} cluster but only once or twice elsewhere, the conditions in the countries in this cluster are characterised by good skiing conditions. The words “rain” and “wet” are used in all of the reports in the {Andorra, Austria, France, Italy} cluster but not in any other reports, characterising the conditions in these countries as being spoiled by rainy conditions. 
   
     
       
             
           
             
             
             
             
             
             
             
             
             
             
             
           
         
             
               TABLE 3 
             
           
           
             
                 
             
             
               Similarity matrix of language usage between snow reports of different countries. 
             
           
        
         
             
               COUNTRY 
               AM 
               AN 
               AUS 
               BUL 
               CAN 
               FRA 
               GER 
               IT 
               NOR 
               SZ 
             
             
                 
             
             
               AMERICA 
               1.00 
               0.21 
               0.44 
               0.05 
               0.50 
               0.22 
               0.40 
               0.35 
               0.18 
               0.31 
             
             
               ANDORRA 
               0.21 
               1.00 
               0.24 
               0.13 
               0.35 
               0.36 
               0.32 
               0.26 
               0.10 
               0.24 
             
             
               AUSTRIA 
               0.44 
               0.24 
               1.00 
               0.08 
               0.32 
               0.54 
               0.21 
               0.42 
               0.22 
               0.28 
             
             
               BULGARIA 
               0.05 
               0.13 
               0.08 
               1.00 
               0.12 
               0.16 
               0.13 
               0.07 
               0.07 
               0.28 
             
             
               CANADA 
               0.50 
               0.35 
               0.32 
               0.12 
               1.00 
               0.29 
               0.53 
               0.39 
               0.20 
               0.45 
             
             
               FRANCE 
               0.22 
               0.36 
               0.54 
               0.16 
               0.29 
               1.00 
               0.26 
               0.40 
               0.13 
               0.35 
             
             
               GERMANY 
               0.40 
               0.32 
               0.21 
               0.13 
               0.53 
               0.26 
               1.00 
               0.21 
               0.22 
               0.50 
             
             
               ITALY 
               0.35 
               0.26 
               0.42 
               0.07 
               0.39 
               0.40 
               0.21 
               1.00 
               0.17 
               0.16 
             
             
               NORWAY 
               0.18 
               0.10 
               0.22 
               0.07 
               0.20 
               0.13 
               0.22 
               0.17 
               1.00 
               0.27 
             
             
               SWITZERLAND 
               0.31 
               0.24 
               0.28 
               0.28 
               0.45 
               0.35 
               0.50 
               0.16 
               0.27 
               1.00