Extended path-indexing

The performance of a theorem prover crucially depends on the speed of the basic retrieval operations, such as finding terms that are unifiable with (instances of, or more general than) some query term. Among the known indexing methods for term retrieval in deduction systems, Path--Indexing exhibits a good performance in general. However, as Path--Indexing is not a perfect filter, the candidates found by this method have still to be subjected to a unification algorithm in order to detect occur--check failures and indirect clashes. As perfect filters, discrimination trees and abstraction trees thus outperform Path--Indexing in some cases. We present an improved version of Path--Indexing that provides both the query trees and the Path--Index with indirect clash an occur--check information. Thus compared to the standard method we dismiss much more terms as possible candidates

A Survey on Retrieval of Mathematical Knowledge

We present a short survey of the literature on indexing and retrieval of mathematical knowledge, with pointers to 72 papers and tentative taxonomies of both retrieval problems and recurring techniques.Comment: CICM 2015, 20 page

Deduction over Mixed-Level Logic Representations for Text Passage Retrieval

A system is described that uses a mixed-level representation of (part of) meaning of natural language documents (based on standard Horn Clause Logic) and a variable-depth search strategy that distinguishes between the different levels of abstraction in the knowledge representation to locate specific passages in the documents. Mixed-level representations as well as variable-depth search strategies are applicable in fields outside that of NLP.Comment: 8 pages, Proceedings of the Eighth International Conference on Tools with Artificial Intelligence (TAI'96), Los Alamitos C

Interning Ground Terms in XSB

This paper presents an implementation of interning of ground terms in the XSB Tabled Prolog system. This is related to the idea of hash-consing. I describe the concept of interning atoms and discuss the issues around interning ground structured terms, motivating why tabling Prolog systems may change the cost-benefit tradeoffs from those of traditional Prolog systems. I describe the details of the implementation of interning ground terms in the XSB Tabled Prolog System and show some of its performance properties. This implementation achieves the effects of that of Zhou and Have but is tuned for XSB's representations and is arguably simpler.Comment: Proceedings of the 13th International Colloquium on Implementation of Constraint LOgic Programming Systems (CICLOPS 2013), Istanbul, Turkey, August 25, 201

A RE-UNIFICATION OF TWO COMPETING MODELS FOR DOCUMENT RETRIEVAL

Two competing approaches for document retrieval were first identified by Robertson et al (Robertson, Maron et al. 1982) for probabilistic retrieval. We point out the corresponding two competing approaches for the Vector Space Model. In both the probabilistic and Vector Space models, only one of the two competing approaches has received significant research attention, because of the unavailibility of sufficient data to implement the second approach. Because it is now feasible to collect vast amounts of feedback data from users, both approaches are now possible. We therefore re-visit the question of a unification of both approaches, for both probabilistic and Vector Space models. This unification of approaches differs from that originally proposed in (Robertson, Maron et al. 1982), and offers unique advantages. Preliminary results of a simulation experiment are reported, and an outline is provided of an ongoing field study.Information Systems Working Papers Serie

From media crossing to media mining

This paper reviews how the concept of Media Crossing has contributed to the advancement of the application domain of information access and explores directions for a future research agenda. These will include themes that could help to broaden the scope and to incorporate the concept of medium-crossing in a more general approach that not only uses combinations of medium-specific processing, but that also exploits more abstract medium-independent representations, partly based on the foundational work on statistical language models for information retrieval. Three examples of successful applications of media crossing will be presented, with a focus on the aspects that could be considered a first step towards a generalized form of media mining