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<HTML> <HEAD> <!--SCRIPT LANGUAGE="JavaScript" SRC="http://a1835.g.akamai.net/f/1835/276/3h/www.netlibrary.com/include/js/dictionary_library.js"></SCRIPT> <SCRIPT LANGUAGE="JavaScript"> if (!opener){document.onkeyup=parent.turnBookPage;} </SCRIPT!--> <META HTTP-EQUIV="Cache-Control" CONTENT="no-cache"> <META HTTP-EQUIV="Pragma" CONTENT="no-cache"> <META HTTP-EQUIV="Expires" CONTENT="-1"><META http-equiv="Content-Type" content="text/html; charset=windows-1252"><SCRIPT>var PrevPage="Page_8";var NextPage="Page_10";var CurPage="Page_9";var PageOrder="21";</SCRIPT> <TITLE>Document</TITLE> </HEAD> <BODY BGCOLOR="#FFFFFF"><CENTER><TABLE BORDER=0 WIDTH=100% CELLPADDING=0><TR><TD ALIGN=CENTER> <TABLE BORDER=0 CELLPADDING=2 CELLSPACING=0 WIDTH=100%> <TR> <TD ALIGN=LEFT><A HREF='Page_8.html'>Previous</A></TD> <TD ALIGN=RIGHT><A HREF='Page_10.html'>Next</A></TD> </TR> </TABLE></TD></TR><TR><TD ALIGN=LEFT><P><A NAME='JUMPDEST_Page_9'/><A NAME='{70}'/><TABLE BORDER=0 CELLSPACING=0 CELLPADDING=0 WIDTH='100%'><TR><TD ALIGN=RIGHT><FONT FACE='Times New Roman, Times, Serif' SIZE=2 COLOR=#FF0000>Page 9</FONT></TD></TR></TABLE><A NAME='{71}'/><TABLE BORDER=0 CELLSPACING=0 CELLPADDING=0><TR> <TD ROWSPAN=5></TD> <TD COLSPAN=3 HEIGHT=12></TD> <TD ROWSPAN=5></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR><TD></TD> <TD><FONT FACE='Times New Roman, Times, Serif' SIZE=3>tive models to anticipate customer behavior and preferences. Data mining of customer information is required in order to make decisions about which clients are the most profitable and desirable and what their characteristics are in order to find more customers just like them—the type of customer profiles and business knowledge electronic retailers and advertisers are beginning to expect from the Web after years of heavy investments and marginal ROIs (returns on investment).</FONT></TD><TD></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR> <TD COLSPAN=3 HEIGHT=1></TD></TR></TABLE><A NAME='{72}'/><TABLE BORDER=0 CELLSPACING=0 CELLPADDING=0><TR> <TD ROWSPAN=5></TD> <TD COLSPAN=3 HEIGHT=12></TD> <TD ROWSPAN=5></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR><TD></TD> <TD><FONT FACE='Times New Roman, Times, Serif' SIZE=3>The savviest retailers utilize sophisticated data mining software that is powered by genetic algorithm (GA) technology to optimize their inventory delivery systems based on consumer preferences and profiles. GAs are programs that replicate the process of evolution (selection, crossover, and mutation) in their search for an optimized solution from a given set of items. For example, GAs in combination with neural networks are being used by some retailers to not only control what inventory is placed in what store, but also design the stores themselves, leading to changes in everything from shelf heights to parking spaces. So if GAs can be used to optimize the design and layout of physical stores, such as a Wal-Mart or Sears, think what they could do to optimize the design of a large electronic retailing website like Amazon.</FONT></TD><TD></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR> <TD COLSPAN=3 HEIGHT=1></TD></TR></TABLE><A NAME='{73}'/><TABLE BORDER=0 CELLSPACING=0 CELLPADDING=0><TR> <TD ROWSPAN=5></TD> <TD COLSPAN=3 HEIGHT=12></TD> <TD ROWSPAN=5></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR><TD></TD> <TD><FONT FACE='Times New Roman, Times, Serif' SIZE=3>Several varied attempts are being made to personalize the browsing experience of website visitors, including collaborative filtering (Firefly) and the aggregate pooling of cookies through ad networks (DoubleClick). However, few companies involved in electronic retailing are looking at data mining technology for the analysis, modeling, and prediction of customer behavior. Some major portals are using software from Aptex, which is a spin-off from HNC, the world's largest neural network company, to position the appropriate banner and ad in front of "right" visitors based on Aptex's proprietary text and neural net technology. The cost and maintenance of this sophisticated type of software, however, is too steep for most commercial websites.</FONT></TD><TD></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR> <TD COLSPAN=3 HEIGHT=1></TD></TR></TABLE><A NAME='{74}'/><TABLE BORDER=0 CELLSPACING=0 CELLPADDING=0><TR> <TD ROWSPAN=5></TD> <TD COLSPAN=3 HEIGHT=12></TD> <TD ROWSPAN=5></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR><TD></TD> <TD><FONT FACE='Times New Roman, Times, Serif' SIZE=3>In the end, the mining and identification of your visitors' profiles can provide you an insight into what type of messages, banners, ads, offers, incentives, products, and services you want to place in front of them. Through the analysis of your website data—after it has been commingled with household and demographic information—your firm can begin to compile a profile of your potential future clients. The mining of your web data is also a strategic necessity for creating a lasting relation with your current customers and establishing a profitable online storefront. As previously mentioned, data mining often</FONT><FONT FACE='Times New Roman, Times, Serif' SIZE=3 COLOR=#FFFF00><!-- continue --></FONT></TD><TD></TD></TR><TR> <TD COLSPAN=3></TD></TR><TR> <TD COLSPAN=3 HEIGHT=1></TD></TR></TABLE><A NAME='{75}'/></FORM></P></TD></TR></TABLE><P><FONT SIZE=0 COLOR=WHITE></CENTER><A NAME="bottom"> </A><!-- netLibrary.com Copyright Notice --> </BODY></HTML>⌨️ 快捷键说明
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