private static string updateRecord()
{
string output = "updateRecord\n";
for (int i = 0; i < count; i++)
{
GlobalParse gp = new GlobalParse(titles[i], "v", sampleArticle.ArticleId);
if (!GlobalParseManager.updateRecord(gp))
{
output += "Error! 调用updateRecord对WordContent为\"" + titles[i] + "\"的记录失败！返回值为false。\n";
errorCount++;
return(output);
}
else
{
output += "Ok! 调用updateRecord对WordContent为\"" + titles[i] + "\"的记录成功！返回值为true。\n";
}
gp = GlobalParseManager.selectRecordByWordContent(gp);
if (gp == null)
{
output += "Error! 通过WordContent\"" + titles[i] + "\"查询记录失败！返回值为空。\n";
errorCount++;
continue;
}
if (!gp.Type.Equals("v"))
{
output += "Error! 对WordContent为\"" + titles[i] + "\"的记录更新Type字段失败！Type被更改为" + gp.Type + "。\n";
errorCount++;
}
else
{
output += "Ok! 对WordContent为\"" + titles[i] + "\"的记录更新Type字段成功！Type被更改为" + gp.Type + "。\n";
}
}
return(output);
}
/*
* 输入：一个Article的model实例以及其content字符串
* 输出：执行结果标示符（暂定如下：0表示成功；-1~-5表示不同类型的失败）
* 功能：
* 1、对传入参数标示的文章内容进行分词、词频统计、TF·IDF计算等
* 2、将文章总词数（article表的wordCount字段）更新到Article表中
* 3、将分词结果更新到GlobalParse数据表中，注意参数中的articleNumber字段值要设置好：如果GlobalParse表中尚无该词记录，则
* articleNumber设为1；若GlobalParse表中已有该词记录，则读取其articleNumber并加一再存进去
* 4、将分词结果更新到LocalParse数据表中，注意参数中的count字段值的设置要设置好：如果LocalParse表中尚无该词记录，则
* count设为1；若LocalParse表中已有该词记录，则读取其count并加一再存进去
* 5、对文章进行分类，并将分类结果更新到Article2Group数据表中。若没有任何类别适合该文章，则默认应该将其分到groupId为0的类别中，该类别即“分组失败”类别或“其他”类别（视用户需求而定）
* 6、返回执行结果。请实现者自己定义一下不同的返回值标示何种类型的失败
*
* 用途说明：该函数为私有函数，只被addArticleWrapper函数在将新文章添加到数据库后自动调用，用于解析新文章。
*
*/
private static void parseArticle(Article a, string content)
{
// 在这里先行数据库中读出 各个 primary group 的 关键词列表
List <List <string> > allGroupKeywordList = new List <List <string> >();
List <string[]> allGroup = PrimaryGroupMananger.getAllGroups();
foreach (string[] ag in allGroup)
{
PrimaryGroups g = new PrimaryGroups();
g.GroupId = Convert.ToInt32(ag[0]);
g.GroupName = ag[1];
allGroupKeywordList.Add(PrimaryGroupKeyWordsManager.getKeyWordsOfCertainPrimaryGroup(g));
}
List <String[]> parseList = stringParse(content);
a.WordCount = parseList.Count;
Dictionary <String, Int32> dic = new Dictionary <String, Int32>();
int wordMount = 0;
foreach (String[] tempString in parseList)
{
if (stop_list.Contains(tempString[0]))
{
continue;
}
if (!dic.ContainsKey(tempString[0]))
{
dic.Add(tempString[0], 1);
wordMount++;
}
else
{
int tempInt = dic[tempString[0]];
dic[tempString[0]] = tempInt + 1;
}
}
int articleID = a.ArticleId;
Dictionary <String, Double> tf_idf = new Dictionary <String, Double>();
foreach (KeyValuePair <String, Int32> keyPair in dic)
{
GlobalParse tempGP = new GlobalParse();
tempGP.ArticleNumber = 1; tempGP.WordContent = keyPair.Key; tempGP.Type = "q";
if (GlobalParseManager.addRecord(tempGP) == false)
{
int num = GlobalParseManager.selectRecordByWordContent(tempGP).ArticleNumber + 1;
tempGP.ArticleNumber = num;
GlobalParseManager.updateRecord(tempGP);
}
tempGP = GlobalParseManager.selectRecordByWordContent(tempGP);
LocalParse tempLP = new LocalParse();
tempLP.ArticleId = articleID; tempLP.WordContent = tempGP.WordContent; tempLP.Count = keyPair.Value;
tempLP.Type = "q";
LocalParseManager.addRecord(tempLP);
// Counting tf_idf
int tf_fenzi = tempLP.Count; int tf_fenmu = wordMount;
int total_document_number = ArticleManager.countArticleNum();
int document_number_with_word = tempGP.ArticleNumber;
double tf_idf_value = ((double)tf_fenzi) / tf_fenmu;// *Math.Log((total_document_number / document_number_with_word), Math.E);
tf_idf.Add(keyPair.Key, tf_idf_value);
}
//tf_idf.OrderByDescending(s => s.Value);
double[] answer = new double[allGroup.Count];
for (int i = 0; i < answer.Length; i++)
{
answer[i] = 0;
}
//Console.Write(tf_idf.ElementAt(0).Key);
//Console.WriteLine(other.Count);
for (int i = 0; i < answer.Length; i++)
{
List <string> list = allGroupKeywordList[i];
if (list == null)
{
continue;
}
foreach (String tempS in list)
{
if (tf_idf.ContainsKey(tempS))
{
answer[i] += tf_idf[tempS];
}
}
}
Article2Group a2g = new Article2Group();
a2g.ArticleId = a.ArticleId;
a2g.GroupId = max(answer);
Article2GroupManager.addRecord(a2g);
}