/**
* Toggle artist/studio recommendation
*
* @return View
*/
public function recommend(Request $request)
{
$res['success'] = false;
$res['recommendCount'] = 0;
$user = Auth::user();
$whom = User::find($request->input('id'));
if ($whom) {
$isAlreadyRecommended = Recommend::where('user_id', $whom->id)->where('recommended_by', $user->id)->first();
if ($isAlreadyRecommended) {
$isAlreadyRecommended->delete();
$res['success'] = true;
$res['message'] = 'Unrecommended';
} else {
$recommend = new Recommend();
$recommend->user_id = $whom->id;
$recommend->recommended_by = $user->id;
$recommend->save();
$res['success'] = true;
$res['message'] = 'Recommended';
}
}
$res['recommendCount'] = Recommend::where('user_id', $whom->id)->count();
return $res;
}
public function recommend_analyze()
{
$data = Input::all();
spl_autoload_register(function ($class_name) {
$file_name = str_replace('\\', '/', $class_name);
$file_name = str_replace('_', '/', $file_name);
$file = dirname(__FILE__) . "/src/{$file_name}.php";
if (is_file($file)) {
include $file;
}
});
$tokenizer = new Recommend();
$classifier = new Classifier($tokenizer);
$train = Recommend::all();
// training file here
foreach ($train as $key) {
# code...
$classifier->train($key['label'], $key['context']);
}
// $classifier->train('Hot', 'It is so hot');
// $classifier->train('Cold', 'it is very cold');
$groups = $classifier->classify($data['content']);
$rec = classification::find($groups);
$content = $data['content'];
$nav = new category();
$menu_top = $nav->menu_top($nav->all()->toArray());
$pro = new Product();
$product = $pro->getRecommend($groups);
return view('frontend.pages.result', array('groups' => $groups, 'content' => $content, 'menu_top' => $menu_top, 'rec' => $rec, 'product' => $product));
//return $groups;
}
