DMOZCC.xml is a XML File with all data sets. Each element is composed by: data set Identifier (DatId), document Url (DocUrl), document Title (DocTitulo), document text (DocTexto) and the Topic Name (TopNombre). A sample of a document in the first data set is:

<DMOZCC>
    <DatId>1</DatId>
    <DocUrl>http://euroflax.com/</DocUrl>
    <DocTitulo>Euroflax Industries, Ltd</DocTitulo>
    <DocTexto>India. International merchants in raw cotton, natural and man-made fibers, yarns and textiles. Part of the KKM Group.</DocTexto>
    <TopNombre>Top/Business/Textiles_and_Nonwovens/Fibers/Wholesale_and_Distribution</TopNombre>
  </DMOZCC>

Each data set was preprocessed (remove special characters, lower case filtering, remove stop words and porter stemming algorithm) using Lucene.Net. Then each data set was organized as a Weka file. Download all preprocessed data sets in DMOZCCPP.rar

Some important statistics:

				Classification (%Instances Correctly Classified)			Classification (Weighted Precision)
DS	#Doc	#Top	#Att	J48	NB	SMO	J48	NB	SMO
1	121	4	559	95,868	93,388	96,694	96,633	93,418	96,865
2	133	7	583	69,173	82,707	89,474	73,624	84,654	90,183
3	129	5	658	75,194	88,372	93,023	82,216	89,288	94,358
4	130	9	689	67,692	73,846	83,846	74,139	74,447	87,601
5	108	6	578	75,926	84,259	81,481	78,218	84,485	84,453
6	131	7	694	84,733	94,656	93,893	88,485	94,775	94,252
7	144	6	675	76,389	94,444	93,056	79,574	94,716	93,984
8	161	7	822	75,155	86,957	91,304	81,542	87,54	92,501
9	135	5	614	82,222	91,852	91,111	83,981	92,059	92,131
10	110	6	650	78,182	87,273	89,091	81,391	86,466	92,629
11	139	7	739	83,453	93,525	93,525	85,509	94,044	94,427
12	131	6	731	81,679	90,076	89,313	82,794	90,269	90,037
13	141	6	732	57,143	69,286	66,429	59,157	69,912	67,174
14	111	5	540	81,081	97,297	93,694	87,322	97,387	95,118
15	112	5	629	83,929	86,607	94,643	89,123	87,013	94,943
16	140	4	624	82,857	92,143	93,571	86,807	92,486	93,786
17	116	5	609	78,448	93,966	92,241	79,049	94,254	92,92
18	136	4	796	86,765	90,441	94,118	89,077	90,693	94,443
19	116	7	623	76,724	89,655	93,966	83,045	89,991	94,31
20	116	6	614	75,862	78,448	84,483	76,879	80,124	88,61
21	118	8	575	63,559	71,186	78,814	68,224	72,925	83,678
22	104	5	495	87,5	89,423	93,269	89,151	89,521	93,477
23	128	7	579	82,031	87,5	90,625	87,689	88,774	92,07
24	128	6	684	71,875	82,031	85,156	75,179	82,188	86,416
25	147	7	808	77,551	85,714	87,075	84,191	85,834	88,835
26	119	4	498	71,429	84,034	88,235	72,095	84,507	89,428
27	121	4	497	75,207	91,736	88,43	80,046	91,962	90,062
28	125	8	507	79,2	88	89,6	83,492	88,97	90,757
29	151	8	763	70,861	84,768	89,404	75,598	86,043	90,694
30	133	6	703	77,444	80,451	85,714	78,744	81,538	87,352
31	164	6	616	82,927	93,293	95,732	84,936	93,181	96,048
32	121	6	609	80,165	92,562	90,909	84,449	92,89	91,982
33	134	6	681	73,881	88,06	88,06	75,183	88,689	87,574
34	141	7	703	79,433	85,816	89,362	82,934	87,222	91,357
35	135	5	636	84,444	96,296	97,778	86,107	96,293	97,9
36	122	4	679	85,246	86,885	95,902	87,645	86,705	96,006
37	118	7	641	70,339	72,034	79,661	78,867	70,982	85,089
38	129	7	601	72,868	82,171	86,822	78,072	82,035	88,219
39	136	5	598	80,882	90,441	94,853	84,782	91,361	95,18
40	153	7	761	76,471	85,621	89,542	82,487	86,072	89,747
41	112	3	585	80,357	91,964	91,071	83,152	93,116	92,695
42	140	8	655	79,286	87,143	87,143	85,913	87,068	87,875
43	119	5	564	83,193	90,756	94,118	85,029	90,558	94,624
44	131	4	593	86,26	94,656	93,13	89,405	94,79	94,445
45	108	5	674	75,926	80,556	80,556	80,313	81,866	80,426
46	129	6	679	84,496	87,597	89,147	87,543	87,499	91,334
47	125	7	606	73,6	83,2	86,4	76,133	83,594	87,263
48	137	8	767	81,022	86,861	90,511	86,617	87,232	91,094
49	138	5	648	78,986	89,13	88,406	86,775	90,085	89,577
50	132	10	632	68,182	78,788	76,515	79,373	81,774	88,509
Avg:	129,16	6,02	643,92	78,06	86,96	89,22	81,97	87,47	90,69
Min:	104,00	3,00	495,00	57,14	69,29	66,43	59,16	69,91	67,17
Max:	164,00	10,00	822,00	95,87	97,30	97,78	96,63	97,39	97,90

Cobos, Carlos. Web Document Clustering Data Sets. University of Cauca, June 2011.