WebKB Dataset

Dataset 5: "WebKB"

All Datasets: boost-starai/BoostSRL-Datasets

by: Nandini Ramanan, Alexander L. Hayes

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Table of Contents:

1. Overview
2. Download
3. Setup
4. Modes

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Overview

The Alchemy WebKB Dataset was adapted from a dataset by the same name from Mark Craven's website (from the University of Wisconsin-Madison). WebKB consists of web pages and hyperlinks "from four computer science departments: Cornell University, The University of Texas, The University of Washington, and The University of Wisconsin."

This version contains the necessary background and train/test folders.

Target: faculty

The facts contain information on five labels: courseprof, courseta, project, sameperson, student.

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Download

Download: WebKB.zip (41.1 KB)

• md5sum: 977e62fca51bfa7fe9c27bdf8af5d478

• sha256sum: 7b36e85cc99483a98c68fc868ba9890398339eaca20b48b80e4b56d16ddc1522

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Setup

Linux/Mac:

1. After downloading, unzip WebKB.zip

unzip WebKB.zip

2. If you're using a jar file, move it into the WebKB directory:

mv (jar file) WebKB/

3. Learning:

• java -jar BoostSRL.jar -l -train train/ -target faculty -trees 10

4. Inference:

• java -jar BoostSRL.jar -i -test test/ -model train/models/ -target faculty -trees 10

Windows:

(Coming soon)

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Modes

setParam: loadAllLibraries = false.
setParam: treeDepth=3.
setParam: nodeSize=3.
setParam: numOfClauses=8.
mode:courseprof(-Course, +Person).
mode:courseprof(+Course, -Person).
mode: courseta(+Course, -Person).
mode: courseta(-Course, +Person).
mode:faculty(+Person).
mode:project(-Proj, +Person).
mode:project(+Proj, -Person).
mode:sameperson(-Person, +Person).
mode:student(+Person).

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