目錄TOC\o"1-3"\h\u1緒論 附錄協(xié)同過濾算法完整代碼：@RequestMapping("/filteringResult.action")publicStringfilteringResult(Map<String,Object>map,HttpServletRequestrequest)throwsIOException,TasteException{this.front();try{Filefile=newFile("item.csv");System.out.println(file.getAbsolutePath());FileWriterout=null;Map<String,Object>parameter=newHashMap<String,Object>();parameter.put("limit",0);//搜索參數(shù)parameter.put("start",10000);//搜索參數(shù)List<Comment>evaluatesList=commentService.getAll(parameter);out=newFileWriter(file);for(Commentevaluates:evaluatesList){out.append(evaluates.getUsersid()+","+evaluates.getProductid()+","+evaluates.getScore()+"\r\n");}out.flush();out.close();DataModelmodel=newFileDataModel(file);//數(shù)據(jù)模型輸入IDint類型UserSimilarityuser=newEuclideanDistanceSimilarity(model);//取相似度intNEIGHBORHOOD_NUM=4;///近鄰數(shù)字intRECOMMENDER_NUM=10;//推薦數(shù)量NearestNUserNeighborhoodneighbor=newNearestNUserNeighborhood(NEIGHBORHOOD_NUM,user,model);//領(lǐng)域模型Stringusersid_tt=(String)this.getSession().getAttribute("usersid");intusersid=Integer.parseInt(usersid_tt);List<Product>a_list=newArrayList();//其中model為數(shù)據(jù)模型，neighbor為用戶領(lǐng)域模型，user為相似度模型，Recommenderrecommender=newGenericUserBasedRecommender(model,neighbor,user);///推薦引擎用戶偏好數(shù)據(jù)包含評分UserCFLongPrimitiveIteratoriter=model.getUserIDs();intmax=10;intindex=0;while(iter.hasNext()){index=0;Longuid=iter.nextLong();//如果結(jié)果集里的用戶ID與當前登錄的相同則輸出結(jié)果if(usersid==(uid)){List<RecommendedItem>list=recommender.recommend(uid,RECOMMENDER_NUM);//根據(jù)UID獲取推薦條目System.out.printf("list:size",list.size());System.out.printf("uid:%s",uid);Stringproductids="";//列表循環(huán)結(jié)果集for(RecommendedItemritem:list){System.out.printf("(%s,%f)",ritem.getItemID(),ritem.getValue());//根據(jù)ID,獲取詳細信息Productproduct=productService.getById(String.valueOf(ritem.getItemID()));a_list.add(product);//添加到結(jié)果if(index>=max){break;}}}}map.put("productList",a_l