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<li><a class="reference internal" href="#">数据集特征</a><ul>
<li><a class="reference internal" href="#ratings-dat">评分文件描述(ratings.dat)</a></li>
<li><a class="reference internal" href="#users-dat">用户文件描述(users.dat)</a></li>
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  <div class="section" id="movielens">
<span id="movielens"></span><span id="demo-ml-dataset"></span><h1>MovieLens数据集<a class="headerlink" href="#movielens" title="永久链接至标题"></a></h1>
<p><a class="reference external" href="http://grouplens.org/datasets/movielens/">MovieLens 数据集</a>由GroupLens Research实验室搜集整理。
该数据集包含一些用户信息、电影信息以及电影评分[1-5]。根据数据量规模，该数据及有很多不同的版本。
我们用<a class="reference external" href="http://files.grouplens.org/datasets/movielens/ml-1m.zip">MovieLens 百万数据集</a>作为示例数据
集，其中包含6,000位用户对4,000部电影的1,000,000条评价。该数据集于2003年2月发布。</p>
<div class="section" id="">
<span id="id1"></span><h2>数据集特征<a class="headerlink" href="#" title="永久链接至标题"></a></h2>
<p>在<a class="reference external" href="http://files.grouplens.org/datasets/movielens/ml-1m.zip">ml-1m 数据集</a>中有许多的特征。在[ml-1m 数据集]
(http://files.grouplens.org/datasets/movielens/ml-1m.zip)中的这些数据文件(含有&#8221;.dat&#8221;的后缀)实际上是CSV文件，
分隔符为&#8221;::&#8221;。以下我们翻译数据集网站中README文件的描述:</p>
<div class="section" id="ratings-dat">
<span id="ratings-dat"></span><h3>评分文件描述(ratings.dat)<a class="headerlink" href="#ratings-dat" title="永久链接至标题"></a></h3>
<p>所有的评分数据都包含在&#8221;ratings.dat&#8221;文件中，遵循如下的格式:</p>
<p>用户ID::电影ID::评分::时间戳</p>
<ul class="simple">
<li>用户ID范围从1到6040</li>
<li>电影ID范围从1到3952</li>
<li>评分被调整为5星的规模(只允许整数的星级)</li>
<li>时间戳表示为从1970-01-01(UTC)来的秒数，与time(2)的返回值一致</li>
<li>每位用户至少有20条评分</li>
</ul>
</div>
<div class="section" id="users-dat">
<span id="users-dat"></span><h3>用户文件描述(users.dat)<a class="headerlink" href="#users-dat" title="永久链接至标题"></a></h3>
<p>所有的用户信息都包含在&#8221;users.dat&#8221;文件中，遵循如下的格式:</p>
<p>用户ID::性别::年龄::职业::邮编</p>
<p>所有的人口统计学信息由用户自愿提供，没有进行正确性的检查。只有含有人
口统计学信息的用户才被包含在数据集中。</p>
<ul class="simple">
<li>性别，用&#8221;M&#8221;表示男性，&#8221;F&#8221;表示女性</li>
<li>年龄从下列列表范围中选取:<ul>
<li>1:  &#8220;18岁以下&#8221;</li>
<li>18:  &#8220;18-24岁&#8221;</li>
<li>25:  &#8220;25-34岁&#8221;</li>
<li>35:  &#8220;35-44岁&#8221;</li>
<li>45:  &#8220;45-49岁&#8221;</li>
<li>50:  &#8220;50-55岁&#8221;</li>
<li>56:  &#8220;56+&#8221;</li>
</ul>
</li>
<li>职业从下面所列中选择:<ul>
<li>0:  &#8220;其他&#8221;或不确定</li>
<li>1:  &#8220;学术/教育工作者&#8221;</li>
<li>2:  &#8220;艺术家&#8221;</li>
<li>3:  &#8220;文书工作/管理员&#8221;</li>
<li>4:  &#8220;大学生/研究生&#8221;</li>
<li>5:  &#8220;客户服务&#8221;</li>
<li>6:  &#8220;医生/医疗保健&#8221;</li>
<li>7:  &#8220;行政工作/管理人员&#8221;</li>
<li>8:  &#8220;农民&#8221;</li>
<li>9:  &#8220;操持家务者&#8221;</li>
<li>10:  &#8220;高中毕业生&#8221;</li>
<li>11:  &#8220;律师&#8221;</li>
<li>12:  &#8220;程序员&#8221;</li>
<li>13:  &#8220;退休人员&#8221;</li>
<li>14:  &#8220;销售/市场&#8221;</li>
<li>15:  &#8220;科学家&#8221;</li>
<li>16:  &#8220;自由职业者&#8221;</li>
<li>17:  &#8220;技术员/工程师&#8221;</li>
<li>18:  &#8220;推销员/手工艺者&#8221;</li>
<li>19:  &#8220;无业人士&#8221;</li>
<li>20:  &#8220;作家&#8221;</li>
</ul>
</li>
</ul>
</div>
<div class="section" id="movies-dat">
<span id="movies-dat"></span><h3>电影文件描述(movies.dat)<a class="headerlink" href="#movies-dat" title="永久链接至标题"></a></h3>
<p>所有的电影信息都包含在&#8221;movies.dat&#8221;文件中，遵循如下的格式:</p>
<p>电影ID::电影名称::电影类型</p>
<ul class="simple">
<li>电影名称（包括发行时间）与IMDB网站提供的一致</li>
<li>电影类型如符合多种用管道符号|分割，选自下列类型:<ul>
<li>动作片</li>
<li>冒险片</li>
<li>动画片</li>
<li>儿童片</li>
<li>喜剧片</li>
<li>犯罪片</li>
<li>纪录片</li>
<li>戏剧</li>
<li>奇幻片</li>
<li>黑色电影</li>
<li>恐怖片</li>
<li>音乐剧</li>
<li>悬疑片</li>
<li>浪漫片</li>
<li>科幻片</li>
<li>惊险电影</li>
<li>战争片</li>
<li>西部片</li>
</ul>
</li>
<li>由于意外的副本记录和测试记录，有些电影ID可能与实际电影不相符合</li>
<li>电影大部分是手工输入数据，因此可能会有一些错误和不一致发生</li>
</ul>
</div>
</div>
</div>


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