Entree Chicago Recommendation Data

Donated on 3/8/2000

This data contains a record of user interactions with the Entree Chicago restaurant recommendation system.

Dataset Characteristics

Transactional, Sequential

Subject Area

Other

Associated Tasks

Recommender-Systems

Feature Type

Categorical

# Instances

50672

# Features

-

Dataset Information

Additional Information

This data records interactions with Entree Chicago restaurant recommendation system (originally http://infolab.cs.uchicago.edu/entree) from September, 1996 to April, 1999. The data is organized into files roughly spanning a quarter year -- with Q3 1996 and Q2 1999 each only containing one month. Each line in a session file represents a session of user interaction with the system. The (tab-separated) fields are as follows: Date, IP, Entry point, Rated restaurant1, ..., Rated restaurantN, End point 1. Entry point: Users can use a restaurant from any city as a entry point, but they always get recommendations for Chicago restaurants. The entry point therefore draws from a larger universe of restaurants than the rest of the data. Entry points have the form nnnX, where nnn is a numeric restaurant ID and X is a character A-H that encodes the city. A = Atlanta B = Boston C = Chicago D = Los Angeles E = New Orleans F = New York G = San Francisco H = Washington DC 2. Rated Restaurant: These are all Chicago restaurants. These entries have the form nnnX, where nnn is a numeric restaurant ID and X is a character L-T that encodes the navigation operation. L = browse (move from one restaurant in a list of recommendations to another) M = cheaper (search for a restaurant like this one, but cheaper) N = nicer ( " " , but nicer) O = closer (unused in the production version of the system) P = more traditional (search for a restaurant like this, but serving more traditional cuisine) Q = more creative (search for a restaurant serving more creative cuisine) R = more lively (search for a restaurant with a livelier atmosphere) S = quieter (search for a restaurant with a quieter atmosphere) T = change cuisine (search for a restaurant like this, but serving a different kind of food) Note that with this tweak, we would ideally like to know what cuisine the user wanted to change to, but this information was not recorded. 3. End point: Just the numeric id for the (Chicago) restaurant that the user saw last. In our experiments, we are assuming that this was a good suggestion, but it is also possible that user just gives up. Some potentially useful data is missing. In many cases, we don't know the starting point because the user input a set of selection criteria (such as "inexpensive traditional Mexican") using a form submission, rather than starting from a known restaurant. These queries were not recorded. This is denoted by a 0 in the entry point field. Some sessions do not have a known end point. This is marked by -1 in the end point field. In addition to the user's interactions, there is also data linking the restaurant ID with its name and features such as "fabulous wine lists", "good for younger kids", and "Ethopian" cuisine. This data is stored by city (e.g. Atlanta, Boston, etc.) and is in the following format: restaurant id [tab] restaurant name [tab] restaurant features (3 digits ids separated by spaces)

Has Missing Values?

Yes

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Creators

Robin Burke

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