基于協同過濾的文學推薦系統設計
摘要
隨著信息技術的飛速發展和文學閱讀需求的日益多樣化，構建一個高效、精準的文學推薦系統變得尤為重要。本文采用Spring Boot框架，結合協同過濾算法，設計并實現了一個基于用戶借閱行為和社交論壇互動的文學推薦系統。該系統綜合考慮了用戶信息、圖書分類、圖書詳細信息以及用戶在圖書館的借閱歷史。通過深入挖掘用戶在社交論壇中的互動數據，如論壇分類、帖子內容、回復情況等，系統能夠更全面地理解用戶的閱讀偏好和潛在需求。在此基礎上，系統運用協同過濾算法，根據用戶的歷史借閱記錄和社交論壇行為，為用戶推薦符合其興趣和需求的文學作品。實驗結果表明，該系統能夠有效提升文學作品的推薦準確性，增強用戶的閱讀體驗和滿意度。通過結合社交論壇數據，系統還能夠發現用戶的潛在興趣點，為圖書館提供有針對性的采購和服務建議。本文的研究不僅為文學推薦系統的設計和實現提供了有益的參考，也為圖書館服務模式的創新提供了新的思路。
關鍵詞：文學推薦系統；Java 語言；MySQL 數據庫；
Developing an Intelligent Literary Recommendation Framework Utilizing Collaborative Filtering Techniques
ABSTRACT
With the rapid development of information?and?technology and the increasing diversification of literary reading needs, it has become particularly important to build an efficient and accurate literary recommendation system. In this paper, a literary recommendation system based on user borrowing behavior and social forum interaction is designed and implemented by using the Spring Boot framework and the collaborative filtering algorithm. The system takes into account user information, book classification, book details, and the user's borrowing history in the library. By digging deep into the user's interaction data in social forums, such as forum classification, post content, and replies, the system can more comprehensively understand the user's reading preferences and potential needs. On this basis, the system uses a collaborative filtering algorithm to recommend literary works that meet the user's interests and needs based on the user's historical borrowing records and social forum behaviors. Experimental results show that the system can effectively improve the recommendation accuracy of literary works and enhance the reading experience and satisfaction of users. By combining data from social forums, the system is also able to discover users' potential interests and provide targeted purchasing and service recommendations for libraries. The research in this paper not only provides a useful reference for the design and implementation of the literary recommendation system, but also provides a new idea for the innovation of library service model.
Keywords: literary recommendation system; Java language; MySQL database;
目 ?錄
第 1 章?緒論 5
1.1 研究背景 5?
1.2國內外發展現狀 5?
1.3 研究意義 6?
1.4 論文設計框架 6?
第 2 章 系統開發技術 8
2.1 Spring Boot框架 8?
2.2 Java語言介紹 8?
2.3 VUE框架簡介 8?2.4?協同過濾 8
第 3 章 系統分析 10
?3.1 可行性分析 10?
3.1.1 技術可行性 10
3.1.2 經濟可行性 10
3.1.3 操作可行性 10?
3.1.4 法律可行性 10?
3.2 系統功能需求 11?
3.2.1 管理員功能需求 11
3.2.2 用戶功能需求 12?
3.3 系統性能分析 12?
第 4 章 系統概要設計 13
4.1 系統結構設計 13?
4.2 系統順序圖設計 13?
4.3 系統流程設計 15
4.3.1 注冊流程 15
4.3.2 登錄流程 16??
4.4 數據庫設計 16?
4.4.1 實體 E-R 圖 16?
4.4.2 數據庫表設計 19?
第 5 章 詳細設計與實現 29
5.1 前臺用戶實現模塊 29?
5.2 后臺管理員實現模塊 31??
第 6 章 系統測試 34
6.1 測試目的 34?
6.2 測試步驟 34?
6.3 測試原則 34?
6.4 測試結論 36?
結論與展望 37
參考文獻 38
部分代碼：
public R autoSort2(@RequestParam Map<String, Object> params,NewsEntity news, HttpServletRequest request){
????????String userId = request.getSession().getAttribute("userId").toString();
????????String inteltypeColumn = "typename";
????????// 查詢收藏集合
????????List<StoreupEntity> storeups = storeupService.selectList(new EntityWrapper<StoreupEntity>().eq("type", 1).eq("userid", userId).eq("tablename", "news").orderBy("addtime", false));
????????List<String> inteltypes = new ArrayList<String>();
????????Integer limit = params.get("limit")==null?10:Integer.parseInt(params.get("limit").toString());
????????List<NewsEntity> newsList = new ArrayList<NewsEntity>();
????????//去重
????????if(storeups!=null && storeups.size()>0) {
????????????List<String> typeList = new ArrayList<String>();
????????????for(StoreupEntity s : storeups) {
????????????????if(typeList.contains(s.getInteltype())) continue;
????????????????typeList.add(s.getInteltype());
????????????????newsList.addAll(newsService.selectList(new EntityWrapper<NewsEntity>().eq(inteltypeColumn, s.getInteltype())));
????????????}
????????}
????????EntityWrapper<NewsEntity> ew = new EntityWrapper<NewsEntity>();
????????params.put("sort", "id");
????????params.put("order", "desc");
????????// 根據協同結果查詢結果并返回
????????PageUtils page = newsService.queryPage(params, MPUtil.sort(MPUtil.between(MPUtil.likeOrEq(ew, news), params), params));
????????List<NewsEntity> pageList = (List<NewsEntity>)page.getList();
????????if(newsList.size()<limit) {
????????????int toAddNum = (limit-newsList.size())<=pageList.size()?(limit-newsList.size()):pageList.size();
????????????for(NewsEntity o1 : pageList) {
????????????????boolean addFlag = true;
????????????????for(NewsEntity o2 : newsList) {
????????????????????if(o1.getId().intValue()==o2.getId().intValue()) {
????????????????????????addFlag = false;
????????????????????????break;
????????????????????}
????????????????}
????????????????if(addFlag) {
????????????????????newsList.add(o1);
????????????????????if(--toAddNum==0) break;
????????????????}
????????????}
????????} else if(newsList.size()>limit) {
????????????newsList = newsList.subList(0, limit);
????????}
????????page.setList(newsList);
????????return R.ok().put("data", page);
????}
}
