A comparison of sub-word indexing methods for information retrieval

This paper compares different methods of subword indexing and their performance on the English and German domain-specific document collection of the Cross-language Evaluation Forum (CLEF). Four major methods to index sub-words are investigated and compared to indexing stems: 1) sequences of vowels and consonants, 2) a dictionary-based approach for decompounding, 3) overlapping character n-grams, and 4) Knuth’s algorithm for hyphenation. The performance and effects of sub-word extraction on search time and index size and time are reported for English and German retrieval experiments. The main results are: For English, indexing sub-words does not outperform the baseline using standard retrieval on stemmed word forms (–8% mean average precision (MAP), – 11% geometric MAP (GMAP), +1% relevant and retrieved documents (rel ret) for the best experiment). For German, with the exception of n-grams, all methods for indexing sub-words achieve a higher performance than the stemming baseline. The best performing sub-word indexing methods are to use consonant-vowelconsonant sequences and index them together with word stems (+17% MAP, +37% GMAP, +14% rel ret compared to the baseline), or to index syllable-like sub-words obtained from the hyphenation algorithm together with stems (+9% MAP, +23% GMAP, +11% rel ret).