Hi Michael, Please correct me if I am wrong, I think what you are trying to say with multimodal search is to combine both text search and vector search to improve the accuracy of search results. As per my understanding of search space people are coining this as Hybrid search. We recently launched a query clause in OpenSearch called "hybrid" which takes this hybrid approach and combines scores of text and vector search globally( https://opensearch.org/blog/hybrid-search/). As per our experiments we saw accuracy being better than text search and vector search alone. Just curious if you are thinking something like this or you have a completely different thought.
I agree that currently to improve the accuracy of search results there have been techniques like re-ranking that are very popular. Thanks Navneet On Fri, Oct 13, 2023 at 8:53 AM Michael Wechner <michael.wech...@wyona.com> wrote: > Thanks for your feedback and the link to the OpenSearch implementation! > > I think the embedding approach as it exists today is not and will not be > able to provide good enough accuracy. > Many people try to fix this with re-ranking, which helps, but does not > really fix the actual problem. > > I think we focus too much on text, because text/language is actually just > a representation of the "models" we create in our minds from the reality we > perceive via our senses. > > When you take multimodality into account from the very beginning, then you > will be forced to approach search differently > and I would argue that this will lead to a much more powerful search > implementation, which is able to provide better accuracy and also the > capability that the implementation knows much better what it does not know. > > I do not mean to sound philosophical, but actually have a quite clear > implementation in my mind resp. on paper, but I would be interested > to know whether the Lucene community is interested to reconsider search > from the ground up? > > I think the Lucene community has a fantastic knowledge / expertise, but I > think it is time to evolve quite radically, and not just do another vector > search implementation. > > WDYT? > > Thanks > > Michael > > > > > > > > Am 13.10.23 um 00:49 schrieb Michael Froh: > > We recently added multimodal search in OpenSearch: > https://github.com/opensearch-project/neural-search/pull/359 > > Since Lucene ultimately just cares about embeddings, does Lucene itself > really need to be multimodal? Wherever the embeddings come from, Lucene can > index the vectors and combine with textual queries, right? > > Thanks, > Froh > > On Thu, Oct 12, 2023 at 12:59 PM Michael Wechner < > michael.wech...@wyona.com> wrote: > >> Hi >> >> Did anyone of the Lucene committers consider making Lucene multimodal? >> >> With a quick Google search I found for example >> >> https://dl.acm.org/doi/abs/10.1145/3503161.3548768 >> >> https://sigir-ecom.github.io/ecom2018/ecom18Papers/paper7.pdf >> >> Thanks >> >> Michael >> >> >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org >> For additional commands, e-mail: dev-h...@lucene.apache.org >> >> >
