{'fraction_non_alphanumeric': 0.021374045801526718, 'fraction_numerical': 0.0, 'mean_word_length': 4.826666666666667, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Resource Selection in Federated Web Search

The current world values data, now more than ever. Data has become an integral part of everyone’s day-to-day lives. The data which is processed, organized and structured or presented in a given context is information. Information is both being collected as well as generated at exponential rates every second. With this spike in interest in information, retrieving it is a key field of study. Information retrieval is the technique of obtaining information relevant to a query from a collection of information resources. To achieve high accuracy in providing users with information, sub- collections of data called verticals are often employed. Common verticals include news, health, academic, jobs, shopping, etc. Our primary goal is to extract information that is most relevant to the specified query. Federated web search is an information retrieval technology to scour through several search engines and databases for every query posed by the user. It then aggregates these results for presentation to the user. Our aim is to implement one of the tasks in federated web search that is resource selection. We need to select the right search engine for a given query; from various search engines available today. This is the purpose of the resource selection task.